Overview

Dataset statistics

Number of variables173
Number of observations235682
Missing cells22644924
Missing cells (%)55.5%
Duplicate rows26197
Duplicate rows (%)11.1%
Total size in memory1.5 GiB
Average record size in memory6.5 KiB

Variable types

DateTime5
Numeric5
Categorical96
Text66
Unsupported1

Alerts

CO_PS_VGM has constant value ""Constant
LO_PS_VGM has constant value ""Constant
DT_VGM has constant value ""Constant
AN_PARA2 has constant value ""Constant
AN_OUTRO has constant value ""Constant
Dataset has 26197 (11.1%) duplicate rowsDuplicates
SEM_NOT is highly overall correlated with SEM_PRI and 2 other fieldsHigh correlation
SEM_PRI is highly overall correlated with SEM_NOT and 1 other fieldsHigh correlation
CO_MUN_RES is highly overall correlated with SG_UF_NOT and 13 other fieldsHigh correlation
PNEUMOPATI is highly overall correlated with CS_ESCOL_N and 66 other fieldsHigh correlation
RES_AN is highly overall correlated with PCR_VSR and 16 other fieldsHigh correlation
SG_UF_NOT is highly overall correlated with CO_MUN_RES and 13 other fieldsHigh correlation
CS_SEXO is highly overall correlated with TP_IDADE and 24 other fieldsHigh correlation
TP_IDADE is highly overall correlated with CS_SEXO and 40 other fieldsHigh correlation
CS_GESTANT is highly overall correlated with CS_SEXO and 18 other fieldsHigh correlation
CS_RACA is highly overall correlated with SURTO_SG and 5 other fieldsHigh correlation
CS_ESCOL_N is highly overall correlated with PNEUMOPATI and 30 other fieldsHigh correlation
ID_PAIS is highly overall correlated with CS_SEXO and 40 other fieldsHigh correlation
CO_PAIS is highly overall correlated with CO_MUN_RES and 37 other fieldsHigh correlation
SG_UF is highly overall correlated with CO_MUN_RES and 39 other fieldsHigh correlation
CS_ZONA is highly overall correlated with ID_PAIS and 16 other fieldsHigh correlation
SURTO_SG is highly overall correlated with SEM_NOT and 41 other fieldsHigh correlation
NOSOCOMIAL is highly overall correlated with PAIS_VGMHigh correlation
AVE_SUINO is highly overall correlated with SURTO_SG and 2 other fieldsHigh correlation
FEBRE is highly overall correlated with CS_SEXO and 22 other fieldsHigh correlation
GARGANTA is highly overall correlated with PAIS_VGM and 3 other fieldsHigh correlation
DISPNEIA is highly overall correlated with SURTO_SG and 2 other fieldsHigh correlation
DESC_RESP is highly overall correlated with SURTO_SG and 4 other fieldsHigh correlation
SATURACAO is highly overall correlated with CS_ESCOL_N and 10 other fieldsHigh correlation
DIARREIA is highly overall correlated with VOMITOHigh correlation
VOMITO is highly overall correlated with TP_IDADE and 15 other fieldsHigh correlation
OUTRO_SIN is highly overall correlated with SURTO_SG and 18 other fieldsHigh correlation
PUERPERA is highly overall correlated with PNEUMOPATI and 30 other fieldsHigh correlation
FATOR_RISC is highly overall correlated with PNEUMOPATI and 41 other fieldsHigh correlation
CARDIOPATI is highly overall correlated with PNEUMOPATI and 26 other fieldsHigh correlation
HEMATOLOGI is highly overall correlated with PNEUMOPATI and 30 other fieldsHigh correlation
SIND_DOWN is highly overall correlated with PNEUMOPATI and 40 other fieldsHigh correlation
HEPATICA is highly overall correlated with PNEUMOPATI and 32 other fieldsHigh correlation
ASMA is highly overall correlated with PNEUMOPATI and 21 other fieldsHigh correlation
DIABETES is highly overall correlated with PNEUMOPATI and 27 other fieldsHigh correlation
NEUROLOGIC is highly overall correlated with PNEUMOPATI and 26 other fieldsHigh correlation
IMUNODEPRE is highly overall correlated with OUTRO_SIN and 25 other fieldsHigh correlation
RENAL is highly overall correlated with PNEUMOPATI and 23 other fieldsHigh correlation
OBESIDADE is highly overall correlated with PNEUMOPATI and 29 other fieldsHigh correlation
OUT_MORBI is highly overall correlated with PNEUMOPATI and 40 other fieldsHigh correlation
VACINA is highly overall correlated with CO_MUN_RES and 24 other fieldsHigh correlation
MAE_VAC is highly overall correlated with PNEUMOPATI and 43 other fieldsHigh correlation
M_AMAMENTA is highly overall correlated with PNEUMOPATI and 35 other fieldsHigh correlation
ANTIVIRAL is highly overall correlated with PNEUMOPATI and 29 other fieldsHigh correlation
TP_ANTIVIR is highly overall correlated with PNEUMOPATI and 30 other fieldsHigh correlation
HOSPITAL is highly overall correlated with PNEUMOPATI and 43 other fieldsHigh correlation
SG_UF_INTE is highly overall correlated with CO_MUN_RES and 36 other fieldsHigh correlation
UTI is highly overall correlated with PNEUMOPATI and 15 other fieldsHigh correlation
SUPORT_VEN is highly overall correlated with CO_MUN_RES and 23 other fieldsHigh correlation
RAIOX_RES is highly overall correlated with PNEUMOPATI and 10 other fieldsHigh correlation
AMOSTRA is highly overall correlated with CO_MUN_RES and 37 other fieldsHigh correlation
TP_AMOSTRA is highly overall correlated with CS_SEXO and 23 other fieldsHigh correlation
PCR_RESUL is highly overall correlated with PNEUMOPATI and 34 other fieldsHigh correlation
POS_PCRFLU is highly overall correlated with PNEUMOPATI and 32 other fieldsHigh correlation
TP_FLU_PCR is highly overall correlated with PNEUMOPATI and 29 other fieldsHigh correlation
PCR_FLUASU is highly overall correlated with PNEUMOPATI and 24 other fieldsHigh correlation
PCR_FLUBLI is highly overall correlated with PNEUMOPATI and 25 other fieldsHigh correlation
POS_PCROUT is highly overall correlated with PNEUMOPATI and 28 other fieldsHigh correlation
PCR_VSR is highly overall correlated with PNEUMOPATI and 46 other fieldsHigh correlation
PCR_PARA1 is highly overall correlated with PNEUMOPATI and 59 other fieldsHigh correlation
PCR_PARA2 is highly overall correlated with PNEUMOPATI and 52 other fieldsHigh correlation
PCR_PARA3 is highly overall correlated with PNEUMOPATI and 47 other fieldsHigh correlation
PCR_PARA4 is highly overall correlated with PNEUMOPATI and 47 other fieldsHigh correlation
PCR_ADENO is highly overall correlated with PNEUMOPATI and 56 other fieldsHigh correlation
PCR_METAP is highly overall correlated with PNEUMOPATI and 48 other fieldsHigh correlation
PCR_BOCA is highly overall correlated with CO_MUN_RES and 61 other fieldsHigh correlation
PCR_RINO is highly overall correlated with CO_MUN_RES and 62 other fieldsHigh correlation
PCR_OUTRO is highly overall correlated with CO_MUN_RES and 60 other fieldsHigh correlation
CLASSI_FIN is highly overall correlated with PNEUMOPATI and 41 other fieldsHigh correlation
CRITERIO is highly overall correlated with PNEUMOPATI and 29 other fieldsHigh correlation
EVOLUCAO is highly overall correlated with PNEUMOPATI and 38 other fieldsHigh correlation
HISTO_VGM is highly overall correlated with PNEUMOPATI and 52 other fieldsHigh correlation
PAIS_VGM is highly overall correlated with SEM_NOT and 27 other fieldsHigh correlation
PCR_SARS2 is highly overall correlated with PNEUMOPATI and 54 other fieldsHigh correlation
DOR_ABD is highly overall correlated with PNEUMOPATI and 14 other fieldsHigh correlation
FADIGA is highly overall correlated with PNEUMOPATI and 9 other fieldsHigh correlation
PERD_OLFT is highly overall correlated with PNEUMOPATI and 19 other fieldsHigh correlation
PERD_PALA is highly overall correlated with PNEUMOPATI and 15 other fieldsHigh correlation
TOMO_RES is highly overall correlated with PNEUMOPATI and 21 other fieldsHigh correlation
TP_TES_AN is highly overall correlated with PNEUMOPATI and 26 other fieldsHigh correlation
POS_AN_FLU is highly overall correlated with PNEUMOPATI and 27 other fieldsHigh correlation
TP_FLU_AN is highly overall correlated with PNEUMOPATI and 19 other fieldsHigh correlation
POS_AN_OUT is highly overall correlated with PNEUMOPATI and 19 other fieldsHigh correlation
AN_SARS2 is highly overall correlated with PNEUMOPATI and 56 other fieldsHigh correlation
AN_VSR is highly overall correlated with RES_AN and 61 other fieldsHigh correlation
AN_PARA1 is highly overall correlated with RES_AN and 48 other fieldsHigh correlation
AN_PARA3 is highly overall correlated with RES_AN and 46 other fieldsHigh correlation
AN_ADENO is highly overall correlated with PNEUMOPATI and 50 other fieldsHigh correlation
TP_AM_SOR is highly overall correlated with SG_UF_NOT and 11 other fieldsHigh correlation
TP_SOR is highly overall correlated with CO_MUN_RES and 28 other fieldsHigh correlation
RES_IGG is highly overall correlated with PNEUMOPATI and 29 other fieldsHigh correlation
RES_IGM is highly overall correlated with PNEUMOPATI and 25 other fieldsHigh correlation
RES_IGA is highly overall correlated with PNEUMOPATI and 25 other fieldsHigh correlation
ESTRANG is highly overall correlated with CO_MUN_RES and 37 other fieldsHigh correlation
VACINA_COV is highly overall correlated with PNEUMOPATI and 43 other fieldsHigh correlation
FNT_IN_COV is highly overall correlated with PNEUMOPATI and 28 other fieldsHigh correlation
FAB_COVRF2 is highly overall correlated with PNEUMOPATI and 17 other fieldsHigh correlation
TRAT_COV is highly overall correlated with PNEUMOPATI and 18 other fieldsHigh correlation
TIPO_TRAT is highly overall correlated with PNEUMOPATI and 13 other fieldsHigh correlation
CS_SEXO is highly imbalanced (68.4%)Imbalance
TP_IDADE is highly imbalanced (68.3%)Imbalance
CS_GESTANT is highly imbalanced (73.2%)Imbalance
ID_PAIS is highly imbalanced (99.9%)Imbalance
CO_PAIS is highly imbalanced (99.9%)Imbalance
CS_ZONA is highly imbalanced (77.0%)Imbalance
NOSOCOMIAL is highly imbalanced (72.5%)Imbalance
AVE_SUINO is highly imbalanced (64.1%)Imbalance
FEBRE is highly imbalanced (58.0%)Imbalance
TOSSE is highly imbalanced (56.8%)Imbalance
DESC_RESP is highly imbalanced (55.8%)Imbalance
SATURACAO is highly imbalanced (57.1%)Imbalance
DIARREIA is highly imbalanced (63.3%)Imbalance
VOMITO is highly imbalanced (64.1%)Imbalance
OUTRO_SIN is highly imbalanced (57.5%)Imbalance
PUERPERA is highly imbalanced (93.9%)Imbalance
FATOR_RISC is highly imbalanced (64.9%)Imbalance
HEMATOLOGI is highly imbalanced (87.0%)Imbalance
SIND_DOWN is highly imbalanced (90.2%)Imbalance
HEPATICA is highly imbalanced (87.3%)Imbalance
ASMA is highly imbalanced (63.5%)Imbalance
DIABETES is highly imbalanced (58.7%)Imbalance
NEUROLOGIC is highly imbalanced (69.1%)Imbalance
IMUNODEPRE is highly imbalanced (72.3%)Imbalance
RENAL is highly imbalanced (74.4%)Imbalance
OBESIDADE is highly imbalanced (74.8%)Imbalance
OUT_MORBI is highly imbalanced (64.8%)Imbalance
MAE_VAC is highly imbalanced (56.9%)Imbalance
ANTIVIRAL is highly imbalanced (60.0%)Imbalance
TP_ANTIVIR is highly imbalanced (87.9%)Imbalance
HOSPITAL is highly imbalanced (94.4%)Imbalance
UTI is highly imbalanced (58.3%)Imbalance
AMOSTRA is highly imbalanced (89.5%)Imbalance
TP_AMOSTRA is highly imbalanced (87.9%)Imbalance
POS_PCRFLU is highly imbalanced (67.5%)Imbalance
TP_FLU_PCR is highly imbalanced (52.0%)Imbalance
PCR_FLUBLI is highly imbalanced (71.6%)Imbalance
POS_PCROUT is highly imbalanced (78.4%)Imbalance
PCR_VSR is highly imbalanced (99.9%)Imbalance
PCR_PARA1 is highly imbalanced (91.6%)Imbalance
PCR_PARA2 is highly imbalanced (84.6%)Imbalance
PCR_PARA3 is highly imbalanced (98.3%)Imbalance
PCR_PARA4 is highly imbalanced (83.8%)Imbalance
PCR_ADENO is highly imbalanced (98.7%)Imbalance
PCR_METAP is highly imbalanced (98.9%)Imbalance
PCR_BOCA is highly imbalanced (98.1%)Imbalance
PCR_RINO is highly imbalanced (99.7%)Imbalance
PCR_OUTRO is highly imbalanced (98.6%)Imbalance
CRITERIO is highly imbalanced (83.3%)Imbalance
EVOLUCAO is highly imbalanced (72.9%)Imbalance
HISTO_VGM is highly imbalanced (> 99.9%)Imbalance
PCR_SARS2 is highly imbalanced (99.9%)Imbalance
DOR_ABD is highly imbalanced (71.5%)Imbalance
FADIGA is highly imbalanced (55.6%)Imbalance
PERD_OLFT is highly imbalanced (81.4%)Imbalance
PERD_PALA is highly imbalanced (76.9%)Imbalance
TP_TES_AN is highly imbalanced (83.8%)Imbalance
POS_AN_OUT is highly imbalanced (55.1%)Imbalance
AN_SARS2 is highly imbalanced (99.9%)Imbalance
AN_VSR is highly imbalanced (99.7%)Imbalance
AN_PARA1 is highly imbalanced (81.7%)Imbalance
AN_PARA3 is highly imbalanced (68.4%)Imbalance
AN_ADENO is highly imbalanced (85.1%)Imbalance
TP_SOR is highly imbalanced (60.5%)Imbalance
RES_IGG is highly imbalanced (78.6%)Imbalance
RES_IGM is highly imbalanced (76.3%)Imbalance
RES_IGA is highly imbalanced (82.5%)Imbalance
ESTRANG is highly imbalanced (97.2%)Imbalance
VACINA_COV is highly imbalanced (62.8%)Imbalance
FNT_IN_COV is highly imbalanced (83.6%)Imbalance
FAB_COVRF2 is highly imbalanced (64.5%)Imbalance
TRAT_COV is highly imbalanced (54.3%)Imbalance
ID_REGIONA has 29004 (12.3%) missing valuesMissing
CO_REGIONA has 29004 (12.3%) missing valuesMissing
CS_ESCOL_N has 85218 (36.2%) missing valuesMissing
ID_RG_RESI has 26537 (11.3%) missing valuesMissing
CO_RG_RESI has 26538 (11.3%) missing valuesMissing
CS_ZONA has 20515 (8.7%) missing valuesMissing
SURTO_SG has 235677 (> 99.9%) missing valuesMissing
NOSOCOMIAL has 28463 (12.1%) missing valuesMissing
AVE_SUINO has 37461 (15.9%) missing valuesMissing
FEBRE has 33498 (14.2%) missing valuesMissing
TOSSE has 21043 (8.9%) missing valuesMissing
GARGANTA has 66356 (28.2%) missing valuesMissing
DISPNEIA has 31169 (13.2%) missing valuesMissing
DESC_RESP has 38572 (16.4%) missing valuesMissing
SATURACAO has 43417 (18.4%) missing valuesMissing
DIARREIA has 67690 (28.7%) missing valuesMissing
VOMITO has 65811 (27.9%) missing valuesMissing
OUTRO_SIN has 69871 (29.6%) missing valuesMissing
OUTRO_DES has 169256 (71.8%) missing valuesMissing
PUERPERA has 170512 (72.3%) missing valuesMissing
CARDIOPATI has 158886 (67.4%) missing valuesMissing
HEMATOLOGI has 169537 (71.9%) missing valuesMissing
SIND_DOWN has 169741 (72.0%) missing valuesMissing
HEPATICA has 169908 (72.1%) missing valuesMissing
ASMA has 165304 (70.1%) missing valuesMissing
DIABETES has 163162 (69.2%) missing valuesMissing
NEUROLOGIC has 166870 (70.8%) missing valuesMissing
PNEUMOPATI has 167022 (70.9%) missing valuesMissing
IMUNODEPRE has 167973 (71.3%) missing valuesMissing
RENAL has 168861 (71.6%) missing valuesMissing
OBESIDADE has 169987 (72.1%) missing valuesMissing
OBES_IMC has 235131 (99.8%) missing valuesMissing
OUT_MORBI has 158647 (67.3%) missing valuesMissing
MORB_DESC has 193125 (81.9%) missing valuesMissing
VACINA has 111781 (47.4%) missing valuesMissing
DT_UT_DOSE has 227695 (96.6%) missing valuesMissing
MAE_VAC has 220304 (93.5%) missing valuesMissing
DT_VAC_MAE has 235162 (99.8%) missing valuesMissing
M_AMAMENTA has 221321 (93.9%) missing valuesMissing
DT_DOSEUNI has 235453 (99.9%) missing valuesMissing
DT_1_DOSE has 235455 (99.9%) missing valuesMissing
DT_2_DOSE has 235515 (99.9%) missing valuesMissing
ANTIVIRAL has 44488 (18.9%) missing valuesMissing
TP_ANTIVIR has 220347 (93.5%) missing valuesMissing
OUT_ANTIV has 235055 (99.7%) missing valuesMissing
DT_ANTIVIR has 221687 (94.1%) missing valuesMissing
HOSPITAL has 6769 (2.9%) missing valuesMissing
DT_INTERNA has 14757 (6.3%) missing valuesMissing
SG_UF_INTE has 20135 (8.5%) missing valuesMissing
ID_RG_INTE has 47020 (20.0%) missing valuesMissing
CO_RG_INTE has 47019 (20.0%) missing valuesMissing
ID_MN_INTE has 20134 (8.5%) missing valuesMissing
CO_MU_INTE has 20137 (8.5%) missing valuesMissing
UTI has 31152 (13.2%) missing valuesMissing
DT_ENTUTI has 176202 (74.8%) missing valuesMissing
DT_SAIDUTI has 203192 (86.2%) missing valuesMissing
SUPORT_VEN has 32175 (13.7%) missing valuesMissing
RAIOX_RES has 84633 (35.9%) missing valuesMissing
RAIOX_OUT has 217956 (92.5%) missing valuesMissing
DT_RAIOX has 152609 (64.8%) missing valuesMissing
AMOSTRA has 8244 (3.5%) missing valuesMissing
DT_COLETA has 18180 (7.7%) missing valuesMissing
TP_AMOSTRA has 23014 (9.8%) missing valuesMissing
OUT_AMOST has 225163 (95.5%) missing valuesMissing
PCR_RESUL has 21350 (9.1%) missing valuesMissing
DT_PCR has 87355 (37.1%) missing valuesMissing
POS_PCRFLU has 181183 (76.9%) missing valuesMissing
TP_FLU_PCR has 226238 (96.0%) missing valuesMissing
PCR_FLUASU has 229816 (97.5%) missing valuesMissing
FLUASU_OUT has 235630 (> 99.9%) missing valuesMissing
PCR_FLUBLI has 233511 (99.1%) missing valuesMissing
FLUBLI_OUT has 235670 (> 99.9%) missing valuesMissing
POS_PCROUT has 176255 (74.8%) missing valuesMissing
PCR_VSR has 212140 (90.0%) missing valuesMissing
PCR_PARA1 has 235435 (99.9%) missing valuesMissing
PCR_PARA2 has 235566 (> 99.9%) missing valuesMissing
PCR_PARA3 has 234519 (99.5%) missing valuesMissing
PCR_PARA4 has 235612 (> 99.9%) missing valuesMissing
PCR_ADENO has 233929 (99.3%) missing valuesMissing
PCR_METAP has 233150 (98.9%) missing valuesMissing
PCR_BOCA has 234768 (99.6%) missing valuesMissing
PCR_RINO has 225825 (95.8%) missing valuesMissing
PCR_OUTRO has 234057 (99.3%) missing valuesMissing
DS_PCR_OUT has 234160 (99.4%) missing valuesMissing
CLASSI_FIN has 19928 (8.5%) missing valuesMissing
CLASSI_OUT has 233671 (99.1%) missing valuesMissing
CRITERIO has 28823 (12.2%) missing valuesMissing
EVOLUCAO has 34629 (14.7%) missing valuesMissing
DT_EVOLUCA has 51543 (21.9%) missing valuesMissing
DT_ENCERRA has 35512 (15.1%) missing valuesMissing
PAIS_VGM has 235680 (> 99.9%) missing valuesMissing
CO_PS_VGM has 235681 (> 99.9%) missing valuesMissing
LO_PS_VGM has 235681 (> 99.9%) missing valuesMissing
DT_VGM has 235681 (> 99.9%) missing valuesMissing
DT_RT_VGM has 235679 (> 99.9%) missing valuesMissing
PCR_SARS2 has 220464 (93.5%) missing valuesMissing
PAC_COCBO has 233631 (99.1%) missing valuesMissing
PAC_DSCBO has 233629 (99.1%) missing valuesMissing
OUT_ANIM has 234919 (99.7%) missing valuesMissing
DOR_ABD has 69757 (29.6%) missing valuesMissing
FADIGA has 65447 (27.8%) missing valuesMissing
PERD_OLFT has 71752 (30.4%) missing valuesMissing
PERD_PALA has 72013 (30.6%) missing valuesMissing
TOMO_RES has 97974 (41.6%) missing valuesMissing
TOMO_OUT has 228258 (96.8%) missing valuesMissing
DT_TOMO has 212024 (90.0%) missing valuesMissing
TP_TES_AN has 136865 (58.1%) missing valuesMissing
DT_RES_AN has 135776 (57.6%) missing valuesMissing
RES_AN has 25757 (10.9%) missing valuesMissing
POS_AN_FLU has 213225 (90.5%) missing valuesMissing
TP_FLU_AN has 230914 (98.0%) missing valuesMissing
POS_AN_OUT has 210238 (89.2%) missing valuesMissing
AN_SARS2 has 219889 (93.3%) missing valuesMissing
AN_VSR has 230511 (97.8%) missing valuesMissing
AN_PARA1 has 235646 (> 99.9%) missing valuesMissing
AN_PARA2 has 235670 (> 99.9%) missing valuesMissing
AN_PARA3 has 235647 (> 99.9%) missing valuesMissing
AN_ADENO has 235635 (> 99.9%) missing valuesMissing
AN_OUTRO has 235403 (99.9%) missing valuesMissing
DS_AN_OUT has 235427 (99.9%) missing valuesMissing
TP_AM_SOR has 227683 (96.6%) missing valuesMissing
SOR_OUT has 234123 (99.3%) missing valuesMissing
DT_CO_SOR has 230631 (97.9%) missing valuesMissing
TP_SOR has 232167 (98.5%) missing valuesMissing
OUT_SOR has 235059 (99.7%) missing valuesMissing
DT_RES has 231762 (98.3%) missing valuesMissing
RES_IGG has 215951 (91.6%) missing valuesMissing
RES_IGM has 215751 (91.5%) missing valuesMissing
RES_IGA has 216438 (91.8%) missing valuesMissing
ESTRANG has 19856 (8.4%) missing valuesMissing
DOSE_1_COV has 123088 (52.2%) missing valuesMissing
DOSE_2_COV has 133632 (56.7%) missing valuesMissing
DOSE_REF has 167838 (71.2%) missing valuesMissing
FAB_COV_1 has 123297 (52.3%) missing valuesMissing
FAB_COV_2 has 133798 (56.8%) missing valuesMissing
FAB_COVREF has 167965 (71.3%) missing valuesMissing
LAB_PR_COV has 123298 (52.3%) missing valuesMissing
LOTE_1_COV has 123693 (52.5%) missing valuesMissing
LOTE_2_COV has 134130 (56.9%) missing valuesMissing
LOTE_REF has 168192 (71.4%) missing valuesMissing
DOSE_2REF has 197100 (83.6%) missing valuesMissing
FAB_COVRF2 has 197150 (83.7%) missing valuesMissing
LOTE_REF2 has 197136 (83.6%) missing valuesMissing
TRAT_COV has 61044 (25.9%) missing valuesMissing
TIPO_TRAT has 234997 (99.7%) missing valuesMissing
OUT_TRAT has 235291 (99.8%) missing valuesMissing
DT_TRT_COV has 235682 (100.0%) missing valuesMissing
PNEUMOPATI is highly skewed (γ1 = 262.0304585)Skewed
PAIS_VGM is uniformly distributedUniform
DT_TRT_COV is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-09-22 21:36:20.451767
Analysis finished2023-09-22 21:41:02.008290
Duration4 minutes and 41.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct260
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.8 MiB
Minimum2023-01-01 00:00:00
Maximum2023-12-09 00:00:00
2023-09-22T21:41:02.143570image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-22T21:41:02.334045image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

SEM_NOT
Real number (ℝ)

HIGH CORRELATION 

Distinct38
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.731087
Minimum1
Maximum38
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 MiB
2023-09-22T21:41:02.530089image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q111
median19
Q326
95-th percentile34
Maximum38
Range37
Interquartile range (IQR)15

Descriptive statistics

Standard deviation9.3661859
Coefficient of variation (CV)0.5000343
Kurtosis-0.89542435
Mean18.731087
Median Absolute Deviation (MAD)7
Skewness0.045025011
Sum4414580
Variance87.725437
MonotonicityNot monotonic
2023-09-22T21:41:02.717586image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
21 9323
 
4.0%
17 8990
 
3.8%
20 8845
 
3.8%
22 8711
 
3.7%
19 8561
 
3.6%
15 8535
 
3.6%
13 8340
 
3.5%
18 7931
 
3.4%
12 7902
 
3.4%
24 7894
 
3.3%
Other values (28) 150650
63.9%
ValueCountFrequency (%)
1 3099
1.3%
2 4948
2.1%
3 4566
1.9%
4 4279
1.8%
5 4223
1.8%
6 4998
2.1%
7 6163
2.6%
8 6146
2.6%
9 6779
2.9%
10 6835
2.9%
ValueCountFrequency (%)
38 57
 
< 0.1%
37 3396
1.4%
36 3654
1.6%
35 4429
1.9%
34 4894
2.1%
33 4868
2.1%
32 4764
2.0%
31 4728
2.0%
30 4885
2.1%
29 5617
2.4%
Distinct260
Distinct (%)0.1%
Missing1
Missing (%)< 0.1%
Memory size1.8 MiB
Minimum2023-01-01 00:00:00
Maximum2023-12-09 00:00:00
2023-09-22T21:41:03.023874image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-22T21:41:03.398092image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

SEM_PRI
Real number (ℝ)

HIGH CORRELATION 

Distinct38
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean17.841714
Minimum1
Maximum38
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 MiB
2023-09-22T21:41:03.776261image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q111
median18
Q325
95-th percentile34
Maximum38
Range37
Interquartile range (IQR)14

Descriptive statistics

Standard deviation9.3513126
Coefficient of variation (CV)0.52412636
Kurtosis-0.89660212
Mean17.841714
Median Absolute Deviation (MAD)7
Skewness0.084595017
Sum4204953
Variance87.447047
MonotonicityNot monotonic
2023-09-22T21:41:04.149369image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
20 9485
 
4.0%
18 8836
 
3.7%
21 8654
 
3.7%
19 8552
 
3.6%
12 8549
 
3.6%
15 8549
 
3.6%
16 8218
 
3.5%
13 8106
 
3.4%
22 7979
 
3.4%
11 7971
 
3.4%
Other values (28) 150782
64.0%
ValueCountFrequency (%)
1 6465
2.7%
2 5104
2.2%
3 4516
1.9%
4 4107
1.7%
5 4744
2.0%
6 5797
2.5%
7 6548
2.8%
8 6761
2.9%
9 7224
3.1%
10 7548
3.2%
ValueCountFrequency (%)
38 5
 
< 0.1%
37 1105
 
0.5%
36 3193
1.4%
35 3969
1.7%
34 4574
1.9%
33 4789
2.0%
32 4607
2.0%
31 4730
2.0%
30 4294
1.8%
29 4875
2.1%

SG_UF_NOT
Categorical

HIGH CORRELATION 

Distinct29
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size13.3 MiB
SP
67013 
PR
23706 
MG
20279 
RJ
15630 
RS
12572 
Other values (24)
96482 

Length

Max length7
Median length2
Mean length2.000017
Min length1

Characters and Unicode

Total characters471368
Distinct characters19
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowMG
2nd rowRJ
3rd rowSP
4th rowSP
5th rowSP

Common Values

ValueCountFrequency (%)
SP 67013
28.4%
PR 23706
 
10.1%
MG 20279
 
8.6%
RJ 15630
 
6.6%
RS 12572
 
5.3%
CE 12105
 
5.1%
SC 9916
 
4.2%
DF 9835
 
4.2%
BA 9298
 
3.9%
PE 7888
 
3.3%
Other values (19) 47440
20.1%

Length

2023-09-22T21:41:04.558203image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
sp 67013
28.4%
pr 23706
 
10.1%
mg 20279
 
8.6%
rj 15630
 
6.6%
rs 12572
 
5.3%
ce 12105
 
5.1%
sc 9916
 
4.2%
df 9835
 
4.2%
ba 9298
 
3.9%
pe 7888
 
3.3%
Other values (19) 47440
20.1%

Most occurring characters

ValueCountFrequency (%)
P 109913
23.3%
S 102511
21.7%
R 57020
12.1%
M 34684
 
7.4%
G 26407
 
5.6%
E 26334
 
5.6%
A 24651
 
5.2%
C 24322
 
5.2%
J 15630
 
3.3%
B 13256
 
2.8%
Other values (9) 36640
 
7.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 471367
> 99.9%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
P 109913
23.3%
S 102511
21.7%
R 57020
12.1%
M 34684
 
7.4%
G 26407
 
5.6%
E 26334
 
5.6%
A 24651
 
5.2%
C 24322
 
5.2%
J 15630
 
3.3%
B 13256
 
2.8%
Other values (8) 36639
 
7.8%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 471367
> 99.9%
Common 1
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
P 109913
23.3%
S 102511
21.7%
R 57020
12.1%
M 34684
 
7.4%
G 26407
 
5.6%
E 26334
 
5.6%
A 24651
 
5.2%
C 24322
 
5.2%
J 15630
 
3.3%
B 13256
 
2.8%
Other values (8) 36639
 
7.8%
Common
ValueCountFrequency (%)
2 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 471368
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
P 109913
23.3%
S 102511
21.7%
R 57020
12.1%
M 34684
 
7.4%
G 26407
 
5.6%
E 26334
 
5.6%
A 24651
 
5.2%
C 24322
 
5.2%
J 15630
 
3.3%
B 13256
 
2.8%
Other values (9) 36640
 
7.8%

ID_REGIONA
Text

MISSING 

Distinct302
Distinct (%)0.1%
Missing29004
Missing (%)12.3%
Memory size15.3 MiB
2023-09-22T21:41:05.042437image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length50
Median length42
Mean length15.91119
Min length1

Characters and Unicode

Total characters3288493
Distinct characters37
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)< 0.1%

Sample

1st rowLEOPOLDINA
2nd rowGVE XV BAURU
3rd rowGVE XIX MARILIA
4th rowGVE XVII CAMPINAS
5th rowNUCLEO REGIONAL DE SAUDE LESTE
ValueCountFrequency (%)
gve 67013
 
11.1%
de 27554
 
4.6%
i 20891
 
3.5%
capital 18788
 
3.1%
regional 18687
 
3.1%
saude 12849
 
2.1%
crs 12572
 
2.1%
cres 12105
 
2.0%
belo 11910
 
2.0%
horizonte 11910
 
2.0%
Other values (385) 389847
64.5%
2023-09-22T21:41:05.579195image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
398004
12.1%
A 328007
 
10.0%
E 297898
 
9.1%
I 255142
 
7.8%
O 250466
 
7.6%
R 232389
 
7.1%
S 175801
 
5.3%
N 138982
 
4.2%
C 125552
 
3.8%
L 124834
 
3.8%
Other values (27) 961418
29.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 2753759
83.7%
Space Separator 398004
 
12.1%
Decimal Number 134826
 
4.1%
Dash Punctuation 1889
 
0.1%
Other Punctuation 15
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 328007
11.9%
E 297898
10.8%
I 255142
 
9.3%
O 250466
 
9.1%
R 232389
 
8.4%
S 175801
 
6.4%
N 138982
 
5.0%
C 125552
 
4.6%
L 124834
 
4.5%
T 123338
 
4.5%
Other values (13) 701350
25.5%
Decimal Number
ValueCountFrequency (%)
0 58081
43.1%
1 38851
28.8%
2 14151
 
10.5%
5 5470
 
4.1%
7 5224
 
3.9%
3 4187
 
3.1%
6 2905
 
2.2%
4 2716
 
2.0%
9 2199
 
1.6%
8 1042
 
0.8%
Other Punctuation
ValueCountFrequency (%)
. 14
93.3%
/ 1
 
6.7%
Space Separator
ValueCountFrequency (%)
398004
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1889
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2753759
83.7%
Common 534734
 
16.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 328007
11.9%
E 297898
10.8%
I 255142
 
9.3%
O 250466
 
9.1%
R 232389
 
8.4%
S 175801
 
6.4%
N 138982
 
5.0%
C 125552
 
4.6%
L 124834
 
4.5%
T 123338
 
4.5%
Other values (13) 701350
25.5%
Common
ValueCountFrequency (%)
398004
74.4%
0 58081
 
10.9%
1 38851
 
7.3%
2 14151
 
2.6%
5 5470
 
1.0%
7 5224
 
1.0%
3 4187
 
0.8%
6 2905
 
0.5%
4 2716
 
0.5%
9 2199
 
0.4%
Other values (4) 2946
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3288493
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
398004
12.1%
A 328007
 
10.0%
E 297898
 
9.1%
I 255142
 
7.8%
O 250466
 
7.6%
R 232389
 
7.1%
S 175801
 
5.3%
N 138982
 
4.2%
C 125552
 
3.8%
L 124834
 
3.8%
Other values (27) 961418
29.2%

CO_REGIONA
Text

MISSING 

Distinct303
Distinct (%)0.1%
Missing29004
Missing (%)12.3%
Memory size12.9 MiB
2023-09-22T21:41:06.034908image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length26
Median length4
Mean length4.0001355
Min length1

Characters and Unicode

Total characters826740
Distinct characters25
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)< 0.1%

Sample

1st row1453
2nd row1340
3rd row1344
4th row1342
5th row1380
ValueCountFrequency (%)
1331 18788
 
9.1%
1449 11910
 
5.8%
1342 9784
 
4.7%
1519 8111
 
3.9%
1356 7664
 
3.7%
1497 6512
 
3.2%
1354 4780
 
2.3%
1380 4678
 
2.3%
1371 4281
 
2.1%
1332 4083
 
2.0%
Other values (296) 126090
61.0%
2023-09-22T21:41:06.641283image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 253424
30.7%
3 151168
18.3%
4 98547
 
11.9%
5 83208
 
10.1%
9 55904
 
6.8%
6 45927
 
5.6%
7 44318
 
5.4%
8 33782
 
4.1%
2 31834
 
3.9%
0 28600
 
3.5%
Other values (15) 28
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 826712
> 99.9%
Uppercase Letter 23
 
< 0.1%
Space Separator 3
 
< 0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
O 4
17.4%
E 3
13.0%
S 2
8.7%
I 2
8.7%
T 2
8.7%
A 2
8.7%
L 2
8.7%
H 1
 
4.3%
P 1
 
4.3%
R 1
 
4.3%
Other values (3) 3
13.0%
Decimal Number
ValueCountFrequency (%)
1 253424
30.7%
3 151168
18.3%
4 98547
 
11.9%
5 83208
 
10.1%
9 55904
 
6.8%
6 45927
 
5.6%
7 44318
 
5.4%
8 33782
 
4.1%
2 31834
 
3.9%
0 28600
 
3.5%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 826717
> 99.9%
Latin 23
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
O 4
17.4%
E 3
13.0%
S 2
8.7%
I 2
8.7%
T 2
8.7%
A 2
8.7%
L 2
8.7%
H 1
 
4.3%
P 1
 
4.3%
R 1
 
4.3%
Other values (3) 3
13.0%
Common
ValueCountFrequency (%)
1 253424
30.7%
3 151168
18.3%
4 98547
 
11.9%
5 83208
 
10.1%
9 55904
 
6.8%
6 45927
 
5.6%
7 44318
 
5.4%
8 33782
 
4.1%
2 31834
 
3.9%
0 28600
 
3.5%
Other values (2) 5
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 826740
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 253424
30.7%
3 151168
18.3%
4 98547
 
11.9%
5 83208
 
10.1%
9 55904
 
6.8%
6 45927
 
5.6%
7 44318
 
5.4%
8 33782
 
4.1%
2 31834
 
3.9%
0 28600
 
3.5%
Other values (15) 28
 
< 0.1%
Distinct1557
Distinct (%)0.7%
Missing2
Missing (%)< 0.1%
Memory size15.1 MiB
2023-09-22T21:41:07.026162image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length32
Median length26
Mean length9.9864944
Min length3

Characters and Unicode

Total characters2353617
Distinct characters37
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique225 ?
Unique (%)0.1%

Sample

1st rowALEM PARAIBA
2nd rowVOLTA REDONDA
3rd rowJAU
4th rowADAMANTINA
5th rowCAMPINAS
ValueCountFrequency (%)
sao 30434
 
8.1%
paulo 18818
 
5.0%
rio 13253
 
3.5%
do 12406
 
3.3%
de 11544
 
3.1%
brasilia 9841
 
2.6%
horizonte 9519
 
2.5%
belo 9356
 
2.5%
fortaleza 8103
 
2.2%
janeiro 6918
 
1.8%
Other values (1494) 244652
65.3%
2023-09-22T21:41:07.612262image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 399364
17.0%
O 266621
11.3%
R 185303
 
7.9%
I 181615
 
7.7%
E 149170
 
6.3%
139164
 
5.9%
S 136360
 
5.8%
L 111925
 
4.8%
N 110803
 
4.7%
T 90192
 
3.8%
Other values (27) 583100
24.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 2213445
94.0%
Space Separator 139164
 
5.9%
Other Punctuation 641
 
< 0.1%
Dash Punctuation 354
 
< 0.1%
Decimal Number 13
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 399364
18.0%
O 266621
12.0%
R 185303
 
8.4%
I 181615
 
8.2%
E 149170
 
6.7%
S 136360
 
6.2%
L 111925
 
5.1%
N 110803
 
5.0%
T 90192
 
4.1%
U 89191
 
4.0%
Other values (15) 492901
22.3%
Decimal Number
ValueCountFrequency (%)
8 4
30.8%
3 2
15.4%
5 2
15.4%
7 2
15.4%
1 1
 
7.7%
0 1
 
7.7%
2 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
' 637
99.4%
" 2
 
0.3%
; 2
 
0.3%
Space Separator
ValueCountFrequency (%)
139164
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 354
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2213445
94.0%
Common 140172
 
6.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 399364
18.0%
O 266621
12.0%
R 185303
 
8.4%
I 181615
 
8.2%
E 149170
 
6.7%
S 136360
 
6.2%
L 111925
 
5.1%
N 110803
 
5.0%
T 90192
 
4.1%
U 89191
 
4.0%
Other values (15) 492901
22.3%
Common
ValueCountFrequency (%)
139164
99.3%
' 637
 
0.5%
- 354
 
0.3%
8 4
 
< 0.1%
" 2
 
< 0.1%
; 2
 
< 0.1%
3 2
 
< 0.1%
5 2
 
< 0.1%
7 2
 
< 0.1%
1 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2353617
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 399364
17.0%
O 266621
11.3%
R 185303
 
7.9%
I 181615
 
7.7%
E 149170
 
6.3%
139164
 
5.9%
S 136360
 
5.8%
L 111925
 
4.8%
N 110803
 
4.7%
T 90192
 
3.8%
Other values (27) 583100
24.8%
Distinct1579
Distinct (%)0.7%
Missing2
Missing (%)< 0.1%
Memory size14.2 MiB
2023-09-22T21:41:07.995439image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.9999321
Min length1

Characters and Unicode

Total characters1414064
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique236 ?
Unique (%)0.1%

Sample

1st row310150
2nd row330630
3rd row352530
4th row350010
5th row350950
ValueCountFrequency (%)
355030 18787
 
8.0%
530010 9835
 
4.2%
310620 9257
 
3.9%
230440 8103
 
3.4%
330455 6918
 
2.9%
350950 6294
 
2.7%
410690 5808
 
2.5%
261160 4497
 
1.9%
292740 4415
 
1.9%
500270 3605
 
1.5%
Other values (1569) 158161
67.1%
2023-09-22T21:41:08.547754image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 416799
29.5%
3 226848
16.0%
5 171961
12.2%
1 146809
 
10.4%
4 135002
 
9.5%
2 130812
 
9.3%
6 52037
 
3.7%
9 51423
 
3.6%
8 42133
 
3.0%
7 40239
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1414063
> 99.9%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 416799
29.5%
3 226848
16.0%
5 171961
12.2%
1 146809
 
10.4%
4 135002
 
9.5%
2 130812
 
9.3%
6 52037
 
3.7%
9 51423
 
3.6%
8 42133
 
3.0%
7 40239
 
2.8%
Uppercase Letter
ValueCountFrequency (%)
M 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1414063
> 99.9%
Latin 1
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 416799
29.5%
3 226848
16.0%
5 171961
12.2%
1 146809
 
10.4%
4 135002
 
9.5%
2 130812
 
9.3%
6 52037
 
3.7%
9 51423
 
3.6%
8 42133
 
3.0%
7 40239
 
2.8%
Latin
ValueCountFrequency (%)
M 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1414064
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 416799
29.5%
3 226848
16.0%
5 171961
12.2%
1 146809
 
10.4%
4 135002
 
9.5%
2 130812
 
9.3%
6 52037
 
3.7%
9 51423
 
3.6%
8 42133
 
3.0%
7 40239
 
2.8%
Distinct3420
Distinct (%)1.5%
Missing3
Missing (%)< 0.1%
Memory size20.2 MiB
2023-09-22T21:41:08.932431image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length60
Median length46
Mean length32.999487
Min length1

Characters and Unicode

Total characters7777286
Distinct characters39
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique464 ?
Unique (%)0.2%

Sample

1st rowHOSPITAL SAO SALVADOR
2nd rowSECRETARIA MUNICIPAL DE SAUDE DE VOLTA REDONDA
3rd rowSANTA CASA DE JAU
4th rowSANTA CASA DE MIS DE ADAMANTINA NA PROVIDENCIA DE DEUS
5th rowUNIDADE DE PRONTO ATENDIMENTO ANCHIETA METROPOLITANO
ValueCountFrequency (%)
hospital 168222
 
14.3%
de 95516
 
8.1%
municipal 24066
 
2.0%
infantil 23907
 
2.0%
santa 23373
 
2.0%
sao 22809
 
1.9%
da 21969
 
1.9%
do 19847
 
1.7%
dr 18869
 
1.6%
regional 17472
 
1.5%
Other values (3244) 738502
62.9%
2023-09-22T21:41:09.552910image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 999409
12.9%
938873
12.1%
I 680149
 
8.7%
O 635271
 
8.2%
S 508802
 
6.5%
E 505588
 
6.5%
T 428890
 
5.5%
L 413881
 
5.3%
N 413543
 
5.3%
R 375211
 
4.8%
Other values (29) 1877669
24.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 6821761
87.7%
Space Separator 938873
 
12.1%
Decimal Number 16643
 
0.2%
Other Punctuation 6
 
< 0.1%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 999409
14.7%
I 680149
10.0%
O 635271
9.3%
S 508802
 
7.5%
E 505588
 
7.4%
T 428890
 
6.3%
L 413881
 
6.1%
N 413543
 
6.1%
R 375211
 
5.5%
D 337131
 
4.9%
Other values (16) 1523886
22.3%
Decimal Number
ValueCountFrequency (%)
3 3946
23.7%
2 3798
22.8%
1 2814
16.9%
4 2397
14.4%
5 2043
12.3%
6 657
 
3.9%
0 403
 
2.4%
9 270
 
1.6%
8 266
 
1.6%
7 49
 
0.3%
Space Separator
ValueCountFrequency (%)
938873
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6821761
87.7%
Common 955525
 
12.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 999409
14.7%
I 680149
10.0%
O 635271
9.3%
S 508802
 
7.5%
E 505588
 
7.4%
T 428890
 
6.3%
L 413881
 
6.1%
N 413543
 
6.1%
R 375211
 
5.5%
D 337131
 
4.9%
Other values (16) 1523886
22.3%
Common
ValueCountFrequency (%)
938873
98.3%
3 3946
 
0.4%
2 3798
 
0.4%
1 2814
 
0.3%
4 2397
 
0.3%
5 2043
 
0.2%
6 657
 
0.1%
0 403
 
< 0.1%
9 270
 
< 0.1%
8 266
 
< 0.1%
Other values (3) 58
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7777286
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 999409
12.9%
938873
12.1%
I 680149
 
8.7%
O 635271
 
8.2%
S 508802
 
6.5%
E 505588
 
6.5%
T 428890
 
5.5%
L 413881
 
5.3%
N 413543
 
5.3%
R 375211
 
4.8%
Other values (29) 1877669
24.1%
Distinct3672
Distinct (%)1.6%
Missing2
Missing (%)< 0.1%
Memory size14.3 MiB
2023-09-22T21:41:09.936216image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length7
Mean length6.7085328
Min length1

Characters and Unicode

Total characters1581067
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique516 ?
Unique (%)0.2%

Sample

1st row2122677
2nd row6086381
3rd row2791722
4th row2077647
5th row2022877
ValueCountFrequency (%)
2526638 4786
 
2.0%
2688603 2464
 
1.0%
2237571 2253
 
1.0%
26948 2123
 
0.9%
2748223 2087
 
0.9%
15563 2086
 
0.9%
10537 2044
 
0.9%
2691868 1675
 
0.7%
2078325 1651
 
0.7%
2077396 1590
 
0.7%
Other values (3662) 212921
90.3%
2023-09-22T21:41:10.491320image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 288610
18.3%
7 161937
10.2%
0 159302
10.1%
8 155779
9.9%
6 151788
9.6%
5 151616
9.6%
9 133951
8.5%
3 129152
8.2%
1 128077
8.1%
4 120849
7.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1581061
> 99.9%
Other Punctuation 6
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 288610
18.3%
7 161937
10.2%
0 159302
10.1%
8 155779
9.9%
6 151788
9.6%
5 151616
9.6%
9 133951
8.5%
3 129152
8.2%
1 128077
8.1%
4 120849
7.6%
Other Punctuation
ValueCountFrequency (%)
/ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1581067
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 288610
18.3%
7 161937
10.2%
0 159302
10.1%
8 155779
9.9%
6 151788
9.6%
5 151616
9.6%
9 133951
8.5%
3 129152
8.2%
1 128077
8.1%
4 120849
7.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1581067
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 288610
18.3%
7 161937
10.2%
0 159302
10.1%
8 155779
9.9%
6 151788
9.6%
5 151616
9.6%
9 133951
8.5%
3 129152
8.2%
1 128077
8.1%
4 120849
7.6%

CS_SEXO
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct9
Distinct (%)< 0.1%
Missing3
Missing (%)< 0.1%
Memory size13.0 MiB
M
122026 
F
113623 
I
 
24
1
 
1
80
 
1
Other values (4)
 
4

Length

Max length10
Median length1
Mean length1.0000467
Min length1

Characters and Unicode

Total characters235690
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)< 0.1%

Sample

1st rowM
2nd rowM
3rd rowF
4th rowF
5th rowM

Common Values

ValueCountFrequency (%)
M 122026
51.8%
F 113623
48.2%
I 24
 
< 0.1%
1 1
 
< 0.1%
80 1
 
< 0.1%
3 1
 
< 0.1%
15/05/2023 1
 
< 0.1%
2 1
 
< 0.1%
74 1
 
< 0.1%
(Missing) 3
 
< 0.1%

Length

2023-09-22T21:41:10.683752image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:10.882443image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
m 122026
51.8%
f 113623
48.2%
i 24
 
< 0.1%
1 1
 
< 0.1%
80 1
 
< 0.1%
3 1
 
< 0.1%
15/05/2023 1
 
< 0.1%
2 1
 
< 0.1%
74 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
M 122026
51.8%
F 113623
48.2%
I 24
 
< 0.1%
0 3
 
< 0.1%
2 3
 
< 0.1%
1 2
 
< 0.1%
3 2
 
< 0.1%
5 2
 
< 0.1%
/ 2
 
< 0.1%
8 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 235673
> 99.9%
Decimal Number 15
 
< 0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3
20.0%
2 3
20.0%
1 2
13.3%
3 2
13.3%
5 2
13.3%
8 1
 
6.7%
7 1
 
6.7%
4 1
 
6.7%
Uppercase Letter
ValueCountFrequency (%)
M 122026
51.8%
F 113623
48.2%
I 24
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
/ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 235673
> 99.9%
Common 17
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3
17.6%
2 3
17.6%
1 2
11.8%
3 2
11.8%
5 2
11.8%
/ 2
11.8%
8 1
 
5.9%
7 1
 
5.9%
4 1
 
5.9%
Latin
ValueCountFrequency (%)
M 122026
51.8%
F 113623
48.2%
I 24
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 235690
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
M 122026
51.8%
F 113623
48.2%
I 24
 
< 0.1%
0 3
 
< 0.1%
2 3
 
< 0.1%
1 2
 
< 0.1%
3 2
 
< 0.1%
5 2
 
< 0.1%
/ 2
 
< 0.1%
8 1
 
< 0.1%
Other values (2) 2
 
< 0.1%
Distinct32573
Distinct (%)13.8%
Missing77
Missing (%)< 0.1%
Memory size15.1 MiB
2023-09-22T21:41:11.228280image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length42
Median length10
Mean length9.9998939
Min length1

Characters and Unicode

Total characters2356025
Distinct characters28
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5829 ?
Unique (%)2.5%

Sample

1st row19/06/1947
2nd row07/10/1955
3rd row24/08/1950
4th row23/09/1976
5th row17/02/1951
ValueCountFrequency (%)
03/03/2023 276
 
0.1%
02/03/2023 273
 
0.1%
02/02/2023 257
 
0.1%
10/03/2023 248
 
0.1%
09/02/2023 246
 
0.1%
09/03/2023 242
 
0.1%
21/03/2023 240
 
0.1%
06/02/2023 239
 
0.1%
18/03/2023 239
 
0.1%
07/03/2023 239
 
0.1%
Other values (32566) 233111
98.9%
2023-09-22T21:41:11.752988image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 471195
20.0%
0 455645
19.3%
2 418700
17.8%
1 364334
15.5%
9 164002
 
7.0%
3 118079
 
5.0%
5 80641
 
3.4%
4 79394
 
3.4%
6 70262
 
3.0%
8 67242
 
2.9%
Other values (18) 66531
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1884789
80.0%
Other Punctuation 471197
 
20.0%
Uppercase Letter 31
 
< 0.1%
Space Separator 5
 
< 0.1%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 5
16.1%
O 4
12.9%
C 4
12.9%
N 4
12.9%
V 3
9.7%
T 2
 
6.5%
I 2
 
6.5%
S 2
 
6.5%
U 1
 
3.2%
B 1
 
3.2%
Other values (3) 3
9.7%
Decimal Number
ValueCountFrequency (%)
0 455645
24.2%
2 418700
22.2%
1 364334
19.3%
9 164002
 
8.7%
3 118079
 
6.3%
5 80641
 
4.3%
4 79394
 
4.2%
6 70262
 
3.7%
8 67242
 
3.6%
7 66490
 
3.5%
Other Punctuation
ValueCountFrequency (%)
/ 471195
> 99.9%
" 1
 
< 0.1%
; 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2355994
> 99.9%
Latin 31
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
/ 471195
20.0%
0 455645
19.3%
2 418700
17.8%
1 364334
15.5%
9 164002
 
7.0%
3 118079
 
5.0%
5 80641
 
3.4%
4 79394
 
3.4%
6 70262
 
3.0%
8 67242
 
2.9%
Other values (5) 66500
 
2.8%
Latin
ValueCountFrequency (%)
A 5
16.1%
O 4
12.9%
C 4
12.9%
N 4
12.9%
V 3
9.7%
T 2
 
6.5%
I 2
 
6.5%
S 2
 
6.5%
U 1
 
3.2%
B 1
 
3.2%
Other values (3) 3
9.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2356025
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 471195
20.0%
0 455645
19.3%
2 418700
17.8%
1 364334
15.5%
9 164002
 
7.0%
3 118079
 
5.0%
5 80641
 
3.4%
4 79394
 
3.4%
6 70262
 
3.0%
8 67242
 
2.9%
Other values (18) 66531
 
2.8%
Distinct125
Distinct (%)0.1%
Missing4
Missing (%)< 0.1%
Memory size13.1 MiB
2023-09-22T21:41:12.076377image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length16
Median length1
Mean length1.4991556
Min length1

Characters and Unicode

Total characters353318
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)< 0.1%

Sample

1st row75
2nd row67
3rd row72
4th row46
5th row71
ValueCountFrequency (%)
1 27739
 
11.8%
2 19043
 
8.1%
3 15384
 
6.5%
4 13287
 
5.6%
5 11266
 
4.8%
6 9417
 
4.0%
7 8046
 
3.4%
8 6907
 
2.9%
9 5874
 
2.5%
10 5278
 
2.2%
Other values (114) 113439
48.1%
2023-09-22T21:41:12.576010image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 58774
16.6%
7 40525
11.5%
6 38435
10.9%
8 37214
10.5%
2 36479
10.3%
5 33849
9.6%
3 33758
9.6%
4 33157
9.4%
9 23706
6.7%
0 17402
 
4.9%
Other values (13) 19
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 353299
> 99.9%
Uppercase Letter 14
 
< 0.1%
Dash Punctuation 3
 
< 0.1%
Space Separator 2
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
V 2
14.3%
U 2
14.3%
T 2
14.3%
O 1
7.1%
C 1
7.1%
G 1
7.1%
B 1
7.1%
I 1
7.1%
X 1
7.1%
E 1
7.1%
Decimal Number
ValueCountFrequency (%)
1 58774
16.6%
7 40525
11.5%
6 38435
10.9%
8 37214
10.5%
2 36479
10.3%
5 33849
9.6%
3 33758
9.6%
4 33157
9.4%
9 23706
6.7%
0 17402
 
4.9%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 353304
> 99.9%
Latin 14
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 58774
16.6%
7 40525
11.5%
6 38435
10.9%
8 37214
10.5%
2 36479
10.3%
5 33849
9.6%
3 33758
9.6%
4 33157
9.4%
9 23706
6.7%
0 17402
 
4.9%
Other values (2) 5
 
< 0.1%
Latin
ValueCountFrequency (%)
V 2
14.3%
U 2
14.3%
T 2
14.3%
O 1
7.1%
C 1
7.1%
G 1
7.1%
B 1
7.1%
I 1
7.1%
X 1
7.1%
E 1
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 353318
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 58774
16.6%
7 40525
11.5%
6 38435
10.9%
8 37214
10.5%
2 36479
10.3%
5 33849
9.6%
3 33758
9.6%
4 33157
9.4%
9 23706
6.7%
0 17402
 
4.9%
Other values (13) 19
 
< 0.1%

TP_IDADE
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct7
Distinct (%)< 0.1%
Missing6
Missing (%)< 0.1%
Memory size13.0 MiB
3
176393 
2
56160 
1
 
3119
6
 
1
11/02/2023
 
1
Other values (2)
 
2

Length

Max length10
Median length1
Mean length1.0000509
Min length1

Characters and Unicode

Total characters235688
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st row3
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 176393
74.8%
2 56160
 
23.8%
1 3119
 
1.3%
6 1
 
< 0.1%
11/02/2023 1
 
< 0.1%
1341 1
 
< 0.1%
5 1
 
< 0.1%
(Missing) 6
 
< 0.1%

Length

2023-09-22T21:41:12.773113image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:12.944087image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
3 176393
74.8%
2 56160
 
23.8%
1 3119
 
1.3%
6 1
 
< 0.1%
11/02/2023 1
 
< 0.1%
1341 1
 
< 0.1%
5 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
3 176395
74.8%
2 56163
 
23.8%
1 3123
 
1.3%
/ 2
 
< 0.1%
0 2
 
< 0.1%
6 1
 
< 0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 235686
> 99.9%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 176395
74.8%
2 56163
 
23.8%
1 3123
 
1.3%
0 2
 
< 0.1%
6 1
 
< 0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
/ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 235688
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 176395
74.8%
2 56163
 
23.8%
1 3123
 
1.3%
/ 2
 
< 0.1%
0 2
 
< 0.1%
6 1
 
< 0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 235688
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 176395
74.8%
2 56163
 
23.8%
1 3123
 
1.3%
/ 2
 
< 0.1%
0 2
 
< 0.1%
6 1
 
< 0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
Distinct174
Distinct (%)0.1%
Missing5
Missing (%)< 0.1%
Memory size13.7 MiB
2023-09-22T21:41:13.310050image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length42
Median length4
Mean length4.000157
Min length1

Characters and Unicode

Total characters942745
Distinct characters27
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)< 0.1%

Sample

1st row3075
2nd row3067
3rd row3072
4th row3046
5th row3071
ValueCountFrequency (%)
3001 18463
 
7.8%
3002 10385
 
4.4%
2001 9224
 
3.9%
3003 8724
 
3.7%
2002 8611
 
3.7%
3004 7712
 
3.3%
2003 6619
 
2.8%
3005 6359
 
2.7%
2004 5517
 
2.3%
3006 5009
 
2.1%
Other values (169) 149060
63.2%
2023-09-22T21:41:13.885380image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 371125
39.4%
3 210149
22.3%
2 92638
 
9.8%
1 61894
 
6.6%
7 40524
 
4.3%
6 38435
 
4.1%
8 37213
 
3.9%
5 33849
 
3.6%
4 33155
 
3.5%
9 23707
 
2.5%
Other values (17) 56
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 942689
> 99.9%
Uppercase Letter 43
 
< 0.1%
Dash Punctuation 6
 
< 0.1%
Space Separator 6
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 7
16.3%
C 6
14.0%
N 4
9.3%
R 4
9.3%
O 4
9.3%
I 3
7.0%
V 3
7.0%
E 3
7.0%
S 2
 
4.7%
U 2
 
4.7%
Other values (4) 5
11.6%
Decimal Number
ValueCountFrequency (%)
0 371125
39.4%
3 210149
22.3%
2 92638
 
9.8%
1 61894
 
6.6%
7 40524
 
4.3%
6 38435
 
4.1%
8 37213
 
3.9%
5 33849
 
3.6%
4 33155
 
3.5%
9 23707
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 942702
> 99.9%
Latin 43
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 7
16.3%
C 6
14.0%
N 4
9.3%
R 4
9.3%
O 4
9.3%
I 3
7.0%
V 3
7.0%
E 3
7.0%
S 2
 
4.7%
U 2
 
4.7%
Other values (4) 5
11.6%
Common
ValueCountFrequency (%)
0 371125
39.4%
3 210149
22.3%
2 92638
 
9.8%
1 61894
 
6.6%
7 40524
 
4.3%
6 38435
 
4.1%
8 37213
 
3.9%
5 33849
 
3.6%
4 33155
 
3.5%
9 23707
 
2.5%
Other values (3) 13
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 942745
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 371125
39.4%
3 210149
22.3%
2 92638
 
9.8%
1 61894
 
6.6%
7 40524
 
4.3%
6 38435
 
4.1%
8 37213
 
3.9%
5 33849
 
3.6%
4 33155
 
3.5%
9 23707
 
2.5%
Other values (17) 56
 
< 0.1%

CS_GESTANT
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct10
Distinct (%)< 0.1%
Missing7
Missing (%)< 0.1%
Memory size13.0 MiB
6
186954 
5
42256 
9
 
4642
3
 
877
2
 
402
Other values (5)
 
544

Length

Max length6
Median length1
Mean length1.0000424
Min length1

Characters and Unicode

Total characters235685
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row6
2nd row6
3rd row5
4th row5
5th row6

Common Values

ValueCountFrequency (%)
6 186954
79.3%
5 42256
 
17.9%
9 4642
 
2.0%
3 877
 
0.4%
2 402
 
0.2%
1 261
 
0.1%
0 181
 
0.1%
4 100
 
< 0.1%
BRASIL 1
 
< 0.1%
351140 1
 
< 0.1%
(Missing) 7
 
< 0.1%

Length

2023-09-22T21:41:14.083824image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:14.271642image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
6 186954
79.3%
5 42256
 
17.9%
9 4642
 
2.0%
3 877
 
0.4%
2 402
 
0.2%
1 261
 
0.1%
0 181
 
0.1%
4 100
 
< 0.1%
brasil 1
 
< 0.1%
351140 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
6 186954
79.3%
5 42257
 
17.9%
9 4642
 
2.0%
3 878
 
0.4%
2 402
 
0.2%
1 263
 
0.1%
0 182
 
0.1%
4 101
 
< 0.1%
B 1
 
< 0.1%
R 1
 
< 0.1%
Other values (4) 4
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 235679
> 99.9%
Uppercase Letter 6
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 186954
79.3%
5 42257
 
17.9%
9 4642
 
2.0%
3 878
 
0.4%
2 402
 
0.2%
1 263
 
0.1%
0 182
 
0.1%
4 101
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
B 1
16.7%
R 1
16.7%
A 1
16.7%
S 1
16.7%
I 1
16.7%
L 1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 235679
> 99.9%
Latin 6
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
6 186954
79.3%
5 42257
 
17.9%
9 4642
 
2.0%
3 878
 
0.4%
2 402
 
0.2%
1 263
 
0.1%
0 182
 
0.1%
4 101
 
< 0.1%
Latin
ValueCountFrequency (%)
B 1
16.7%
R 1
16.7%
A 1
16.7%
S 1
16.7%
I 1
16.7%
L 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 235685
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 186954
79.3%
5 42257
 
17.9%
9 4642
 
2.0%
3 878
 
0.4%
2 402
 
0.2%
1 263
 
0.1%
0 182
 
0.1%
4 101
 
< 0.1%
B 1
 
< 0.1%
R 1
 
< 0.1%
Other values (4) 4
 
< 0.1%

CS_RACA
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)< 0.1%
Missing6
Missing (%)< 0.1%
Memory size13.0 MiB
1
96381 
4
94027 
9
34892 
2
 
7546
3
 
1743
Other values (2)
 
1087

Length

Max length6
Median length1
Mean length1.0000424
Min length1

Characters and Unicode

Total characters235686
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row9
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 96381
40.9%
4 94027
39.9%
9 34892
 
14.8%
2 7546
 
3.2%
3 1743
 
0.7%
5 1085
 
0.5%
BRASIL 2
 
< 0.1%
(Missing) 6
 
< 0.1%

Length

2023-09-22T21:41:14.449637image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:14.623170image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1 96381
40.9%
4 94027
39.9%
9 34892
 
14.8%
2 7546
 
3.2%
3 1743
 
0.7%
5 1085
 
0.5%
brasil 2
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
1 96381
40.9%
4 94027
39.9%
9 34892
 
14.8%
2 7546
 
3.2%
3 1743
 
0.7%
5 1085
 
0.5%
B 2
 
< 0.1%
R 2
 
< 0.1%
A 2
 
< 0.1%
S 2
 
< 0.1%
Other values (2) 4
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 235674
> 99.9%
Uppercase Letter 12
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 96381
40.9%
4 94027
39.9%
9 34892
 
14.8%
2 7546
 
3.2%
3 1743
 
0.7%
5 1085
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
B 2
16.7%
R 2
16.7%
A 2
16.7%
S 2
16.7%
I 2
16.7%
L 2
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 235674
> 99.9%
Latin 12
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 96381
40.9%
4 94027
39.9%
9 34892
 
14.8%
2 7546
 
3.2%
3 1743
 
0.7%
5 1085
 
0.5%
Latin
ValueCountFrequency (%)
B 2
16.7%
R 2
16.7%
A 2
16.7%
S 2
16.7%
I 2
16.7%
L 2
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 235686
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 96381
40.9%
4 94027
39.9%
9 34892
 
14.8%
2 7546
 
3.2%
3 1743
 
0.7%
5 1085
 
0.5%
B 2
 
< 0.1%
R 2
 
< 0.1%
A 2
 
< 0.1%
S 2
 
< 0.1%
Other values (2) 4
 
< 0.1%

CS_ESCOL_N
Categorical

HIGH CORRELATION  MISSING 

Distinct13
Distinct (%)< 0.1%
Missing85218
Missing (%)36.2%
Memory size11.6 MiB
9
54156 
5
41156 
1
18597 
0
17065 
3
8477 
Other values (8)
11013 

Length

Max length42
Median length1
Mean length1.0006912
Min length1

Characters and Unicode

Total characters150568
Distinct characters28
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)< 0.1%

Sample

1st row9
2nd row9
3rd row1
4th row4
5th row9

Common Values

ValueCountFrequency (%)
9 54156
23.0%
5 41156
17.5%
1 18597
 
7.9%
0 17065
 
7.2%
3 8477
 
3.6%
2 7374
 
3.1%
4 3633
 
1.5%
86 - COVID-19 SINOVAC/BUTANTAN - CORONAVAC 1
 
< 0.1%
SC 1
 
< 0.1%
14/02/2023 1
 
< 0.1%
Other values (3) 3
 
< 0.1%
(Missing) 85218
36.2%

Length

2023-09-22T21:41:14.794281image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
9 54156
36.0%
5 41156
27.4%
1 18597
 
12.4%
0 17065
 
11.3%
3 8477
 
5.6%
2 7374
 
4.9%
4 3633
 
2.4%
2
 
< 0.1%
86 1
 
< 0.1%
covid-19 1
 
< 0.1%
Other values (7) 7
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
9 54157
36.0%
5 41156
27.3%
1 18601
 
12.4%
0 17069
 
11.3%
3 8479
 
5.6%
2 7384
 
4.9%
4 3635
 
2.4%
; 23
 
< 0.1%
" 7
 
< 0.1%
C 6
 
< 0.1%
Other values (18) 51
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 150484
99.9%
Uppercase Letter 39
 
< 0.1%
Other Punctuation 37
 
< 0.1%
Space Separator 5
 
< 0.1%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 6
15.4%
A 5
12.8%
O 5
12.8%
N 4
10.3%
V 4
10.3%
S 4
10.3%
I 3
7.7%
D 2
 
5.1%
T 2
 
5.1%
B 1
 
2.6%
Other values (3) 3
7.7%
Decimal Number
ValueCountFrequency (%)
9 54157
36.0%
5 41156
27.3%
1 18601
 
12.4%
0 17069
 
11.3%
3 8479
 
5.6%
2 7384
 
4.9%
4 3635
 
2.4%
6 2
 
< 0.1%
8 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
; 23
62.2%
" 7
 
18.9%
/ 5
 
13.5%
. 2
 
5.4%
Space Separator
ValueCountFrequency (%)
5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 150529
> 99.9%
Latin 39
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
9 54157
36.0%
5 41156
27.3%
1 18601
 
12.4%
0 17069
 
11.3%
3 8479
 
5.6%
2 7384
 
4.9%
4 3635
 
2.4%
; 23
 
< 0.1%
" 7
 
< 0.1%
/ 5
 
< 0.1%
Other values (5) 13
 
< 0.1%
Latin
ValueCountFrequency (%)
C 6
15.4%
A 5
12.8%
O 5
12.8%
N 4
10.3%
V 4
10.3%
S 4
10.3%
I 3
7.7%
D 2
 
5.1%
T 2
 
5.1%
B 1
 
2.6%
Other values (3) 3
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 150568
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 54157
36.0%
5 41156
27.3%
1 18601
 
12.4%
0 17069
 
11.3%
3 8479
 
5.6%
2 7384
 
4.9%
4 3635
 
2.4%
; 23
 
< 0.1%
" 7
 
< 0.1%
C 6
 
< 0.1%
Other values (18) 51
 
< 0.1%

ID_PAIS
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct23
Distinct (%)< 0.1%
Missing6
Missing (%)< 0.1%
Memory size14.2 MiB
BRASIL
235610 
PARAGUAI
 
25
BOLIVIA
 
18
VENEZUELA
 
3
ARGENTINA
 
2
Other values (18)
 
18

Length

Max length19
Median length6
Mean length6.0003692
Min length1

Characters and Unicode

Total characters1414143
Distinct characters31
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)< 0.1%

Sample

1st rowBRASIL
2nd rowBRASIL
3rd rowBRASIL
4th rowBRASIL
5th rowBRASIL

Common Values

ValueCountFrequency (%)
BRASIL 235610
> 99.9%
PARAGUAI 25
 
< 0.1%
BOLIVIA 18
 
< 0.1%
VENEZUELA 3
 
< 0.1%
ARGENTINA 2
 
< 0.1%
13/02/2023 1
 
< 0.1%
RJ 1
 
< 0.1%
AUSTRIA 1
 
< 0.1%
CHAPECO 1
 
< 0.1%
BRA80;1;26/04/2023" 1
 
< 0.1%
Other values (13) 13
 
< 0.1%
(Missing) 6
 
< 0.1%

Length

2023-09-22T21:41:15.043337image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
brasil 235610
> 99.9%
paraguai 25
 
< 0.1%
bolivia 18
 
< 0.1%
venezuela 3
 
< 0.1%
argentina 2
 
< 0.1%
guiana 2
 
< 0.1%
francesa 1
 
< 0.1%
cuba 1
 
< 0.1%
5 1
 
< 0.1%
peru 1
 
< 0.1%
Other values (13) 13
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
A 235725
16.7%
I 235678
16.7%
R 235644
16.7%
L 235632
16.7%
B 235630
16.7%
S 235614
16.7%
U 38
 
< 0.1%
G 31
 
< 0.1%
P 29
 
< 0.1%
V 21
 
< 0.1%
Other values (21) 101
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1414102
> 99.9%
Decimal Number 33
 
< 0.1%
Other Punctuation 7
 
< 0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 235725
16.7%
I 235678
16.7%
R 235644
16.7%
L 235632
16.7%
B 235630
16.7%
S 235614
16.7%
U 38
 
< 0.1%
G 31
 
< 0.1%
P 29
 
< 0.1%
V 21
 
< 0.1%
Other values (9) 60
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
2 10
30.3%
0 8
24.2%
1 5
15.2%
3 3
 
9.1%
8 2
 
6.1%
4 2
 
6.1%
5 2
 
6.1%
6 1
 
3.0%
Other Punctuation
ValueCountFrequency (%)
/ 4
57.1%
; 2
28.6%
" 1
 
14.3%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1414102
> 99.9%
Common 41
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 235725
16.7%
I 235678
16.7%
R 235644
16.7%
L 235632
16.7%
B 235630
16.7%
S 235614
16.7%
U 38
 
< 0.1%
G 31
 
< 0.1%
P 29
 
< 0.1%
V 21
 
< 0.1%
Other values (9) 60
 
< 0.1%
Common
ValueCountFrequency (%)
2 10
24.4%
0 8
19.5%
1 5
12.2%
/ 4
 
9.8%
3 3
 
7.3%
8 2
 
4.9%
; 2
 
4.9%
4 2
 
4.9%
5 2
 
4.9%
6 1
 
2.4%
Other values (2) 2
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1414143
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 235725
16.7%
I 235678
16.7%
R 235644
16.7%
L 235632
16.7%
B 235630
16.7%
S 235614
16.7%
U 38
 
< 0.1%
G 31
 
< 0.1%
P 29
 
< 0.1%
V 21
 
< 0.1%
Other values (21) 101
 
< 0.1%

CO_PAIS
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct18
Distinct (%)< 0.1%
Missing10
Missing (%)< 0.1%
Memory size13.0 MiB
1
235610 
126
 
25
68
 
18
138
 
3
32
 
2
Other values (13)
 
14

Length

Max length24
Median length1
Mean length1.0005262
Min length1

Characters and Unicode

Total characters235796
Distinct characters25
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 235610
> 99.9%
126 25
 
< 0.1%
68 18
 
< 0.1%
138 3
 
< 0.1%
32 2
 
< 0.1%
2 2
 
< 0.1%
111 1
 
< 0.1%
143 1
 
< 0.1%
1553 1
 
< 0.1%
GO 1
 
< 0.1%
Other values (8) 8
 
< 0.1%
(Missing) 10
 
< 0.1%

Length

2023-09-22T21:41:15.380875image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1 235610
> 99.9%
126 25
 
< 0.1%
68 18
 
< 0.1%
138 3
 
< 0.1%
32 2
 
< 0.1%
2 2
 
< 0.1%
cruzes 1
 
< 0.1%
156 1
 
< 0.1%
7 1
 
< 0.1%
182 1
 
< 0.1%
Other values (12) 12
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
1 235647
99.9%
6 44
 
< 0.1%
2 33
 
< 0.1%
8 23
 
< 0.1%
3 9
 
< 0.1%
4
 
< 0.1%
I 4
 
< 0.1%
G 3
 
< 0.1%
0 3
 
< 0.1%
5 3
 
< 0.1%
Other values (15) 23
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 235768
> 99.9%
Uppercase Letter 22
 
< 0.1%
Space Separator 4
 
< 0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
I 4
18.2%
G 3
13.6%
O 2
9.1%
S 2
9.1%
E 2
9.1%
V 2
9.1%
D 1
 
4.5%
A 1
 
4.5%
M 1
 
4.5%
C 1
 
4.5%
Other values (3) 3
13.6%
Decimal Number
ValueCountFrequency (%)
1 235647
99.9%
6 44
 
< 0.1%
2 33
 
< 0.1%
8 23
 
< 0.1%
3 9
 
< 0.1%
0 3
 
< 0.1%
5 3
 
< 0.1%
9 3
 
< 0.1%
7 2
 
< 0.1%
4 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 235774
> 99.9%
Latin 22
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
I 4
18.2%
G 3
13.6%
O 2
9.1%
S 2
9.1%
E 2
9.1%
V 2
9.1%
D 1
 
4.5%
A 1
 
4.5%
M 1
 
4.5%
C 1
 
4.5%
Other values (3) 3
13.6%
Common
ValueCountFrequency (%)
1 235647
99.9%
6 44
 
< 0.1%
2 33
 
< 0.1%
8 23
 
< 0.1%
3 9
 
< 0.1%
4
 
< 0.1%
0 3
 
< 0.1%
5 3
 
< 0.1%
9 3
 
< 0.1%
/ 2
 
< 0.1%
Other values (2) 3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 235796
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 235647
99.9%
6 44
 
< 0.1%
2 33
 
< 0.1%
8 23
 
< 0.1%
3 9
 
< 0.1%
4
 
< 0.1%
I 4
 
< 0.1%
G 3
 
< 0.1%
0 3
 
< 0.1%
5 3
 
< 0.1%
Other values (15) 23
 
< 0.1%

SG_UF
Categorical

HIGH CORRELATION 

Distinct32
Distinct (%)< 0.1%
Missing67
Missing (%)< 0.1%
Memory size13.3 MiB
SP
66747 
PR
23595 
MG
20520 
RJ
15642 
RS
12584 
Other values (27)
96527 

Length

Max length7
Median length2
Mean length2.0000424
Min length1

Characters and Unicode

Total characters471240
Distinct characters21
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st rowMG
2nd rowRJ
3rd rowSP
4th rowSP
5th rowSP

Common Values

ValueCountFrequency (%)
SP 66747
28.3%
PR 23595
 
10.0%
MG 20520
 
8.7%
RJ 15642
 
6.6%
RS 12584
 
5.3%
CE 12105
 
5.1%
SC 9942
 
4.2%
BA 9369
 
4.0%
DF 8165
 
3.5%
PE 7845
 
3.3%
Other values (22) 49101
20.8%

Length

2023-09-22T21:41:15.751386image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
sp 66747
28.3%
pr 23595
 
10.0%
mg 20520
 
8.7%
rj 15642
 
6.6%
rs 12584
 
5.3%
ce 12105
 
5.1%
sc 9942
 
4.2%
ba 9369
 
4.0%
df 8165
 
3.5%
pe 7845
 
3.3%
Other values (22) 49101
20.8%

Most occurring characters

ValueCountFrequency (%)
P 109515
23.2%
S 102229
21.7%
R 57035
12.1%
M 35145
 
7.5%
G 28136
 
6.0%
E 26225
 
5.6%
A 24878
 
5.3%
C 24238
 
5.1%
J 15642
 
3.3%
B 13343
 
2.8%
Other values (11) 34854
 
7.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 471234
> 99.9%
Decimal Number 6
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
P 109515
23.2%
S 102229
21.7%
R 57035
12.1%
M 35145
 
7.5%
G 28136
 
6.0%
E 26225
 
5.6%
A 24878
 
5.3%
C 24238
 
5.1%
J 15642
 
3.3%
B 13343
 
2.8%
Other values (8) 34848
 
7.4%
Decimal Number
ValueCountFrequency (%)
3 3
50.0%
1 2
33.3%
0 1
 
16.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 471234
> 99.9%
Common 6
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
P 109515
23.2%
S 102229
21.7%
R 57035
12.1%
M 35145
 
7.5%
G 28136
 
6.0%
E 26225
 
5.6%
A 24878
 
5.3%
C 24238
 
5.1%
J 15642
 
3.3%
B 13343
 
2.8%
Other values (8) 34848
 
7.4%
Common
ValueCountFrequency (%)
3 3
50.0%
1 2
33.3%
0 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 471240
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
P 109515
23.2%
S 102229
21.7%
R 57035
12.1%
M 35145
 
7.5%
G 28136
 
6.0%
E 26225
 
5.6%
A 24878
 
5.3%
C 24238
 
5.1%
J 15642
 
3.3%
B 13343
 
2.8%
Other values (11) 34854
 
7.4%

ID_RG_RESI
Text

MISSING 

Distinct322
Distinct (%)0.2%
Missing26537
Missing (%)11.3%
Memory size15.4 MiB
2023-09-22T21:41:16.302313image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length50
Median length43
Mean length15.940505
Min length1

Characters and Unicode

Total characters3333877
Distinct characters36
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)< 0.1%

Sample

1st rowLEOPOLDINA
2nd rowGVE XV BAURU
3rd rowGVE XIX MARILIA
4th rowGVE XVII CAMPINAS
5th rowNUCLEO REGIONAL DE SAUDE LESTE
ValueCountFrequency (%)
gve 66747
 
10.9%
de 29159
 
4.8%
i 19281
 
3.2%
regional 19219
 
3.1%
capital 16956
 
2.8%
saude 13997
 
2.3%
crs 12584
 
2.1%
cres 12105
 
2.0%
belo 11204
 
1.8%
horizonte 11204
 
1.8%
Other values (400) 399139
65.3%
2023-09-22T21:41:17.342565image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
403127
12.1%
A 331622
 
9.9%
E 302458
 
9.1%
I 259061
 
7.8%
O 253986
 
7.6%
R 235096
 
7.1%
S 182734
 
5.5%
N 146895
 
4.4%
C 129132
 
3.9%
T 122575
 
3.7%
Other values (26) 967191
29.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 2793703
83.8%
Space Separator 403127
 
12.1%
Decimal Number 134697
 
4.0%
Dash Punctuation 2325
 
0.1%
Other Punctuation 25
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 331622
11.9%
E 302458
10.8%
I 259061
 
9.3%
O 253986
 
9.1%
R 235096
 
8.4%
S 182734
 
6.5%
N 146895
 
5.3%
C 129132
 
4.6%
T 122575
 
4.4%
L 120313
 
4.3%
Other values (13) 709831
25.4%
Decimal Number
ValueCountFrequency (%)
0 57660
42.8%
1 35795
26.6%
2 15064
 
11.2%
5 5802
 
4.3%
7 5053
 
3.8%
3 4946
 
3.7%
6 3301
 
2.5%
4 2967
 
2.2%
9 2579
 
1.9%
8 1530
 
1.1%
Space Separator
ValueCountFrequency (%)
403127
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2325
100.0%
Other Punctuation
ValueCountFrequency (%)
. 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2793703
83.8%
Common 540174
 
16.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 331622
11.9%
E 302458
10.8%
I 259061
 
9.3%
O 253986
 
9.1%
R 235096
 
8.4%
S 182734
 
6.5%
N 146895
 
5.3%
C 129132
 
4.6%
T 122575
 
4.4%
L 120313
 
4.3%
Other values (13) 709831
25.4%
Common
ValueCountFrequency (%)
403127
74.6%
0 57660
 
10.7%
1 35795
 
6.6%
2 15064
 
2.8%
5 5802
 
1.1%
7 5053
 
0.9%
3 4946
 
0.9%
6 3301
 
0.6%
4 2967
 
0.5%
9 2579
 
0.5%
Other values (3) 3880
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3333877
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
403127
12.1%
A 331622
 
9.9%
E 302458
 
9.1%
I 259061
 
7.8%
O 253986
 
7.6%
R 235096
 
7.1%
S 182734
 
5.5%
N 146895
 
4.4%
C 129132
 
3.9%
T 122575
 
3.7%
Other values (26) 967191
29.0%

CO_RG_RESI
Text

MISSING 

Distinct322
Distinct (%)0.2%
Missing26538
Missing (%)11.3%
Memory size13.0 MiB
2023-09-22T21:41:17.780513image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length7
Median length4
Mean length4.0000048
Min length1

Characters and Unicode

Total characters836577
Distinct characters16
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)< 0.1%

Sample

1st row1453
2nd row1340
3rd row1344
4th row1342
5th row1380
ValueCountFrequency (%)
1331 16956
 
8.1%
1449 11204
 
5.4%
1342 9716
 
4.6%
1356 7045
 
3.4%
1519 5967
 
2.9%
1497 5621
 
2.7%
1354 4411
 
2.1%
1380 4238
 
2.0%
1332 3987
 
1.9%
1333 3965
 
1.9%
Other values (312) 136034
65.0%
2023-09-22T21:41:18.382072image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 252234
30.2%
3 151203
18.1%
4 98895
 
11.8%
5 86240
 
10.3%
9 54103
 
6.5%
6 47615
 
5.7%
7 44176
 
5.3%
2 38038
 
4.5%
8 35338
 
4.2%
0 28728
 
3.4%
Other values (6) 7
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 836570
> 99.9%
Uppercase Letter 7
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 252234
30.2%
3 151203
18.1%
4 98895
 
11.8%
5 86240
 
10.3%
9 54103
 
6.5%
6 47615
 
5.7%
7 44176
 
5.3%
2 38038
 
4.5%
8 35338
 
4.2%
0 28728
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
N 2
28.6%
A 1
14.3%
I 1
14.3%
C 1
14.3%
U 1
14.3%
S 1
14.3%

Most occurring scripts

ValueCountFrequency (%)
Common 836570
> 99.9%
Latin 7
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 252234
30.2%
3 151203
18.1%
4 98895
 
11.8%
5 86240
 
10.3%
9 54103
 
6.5%
6 47615
 
5.7%
7 44176
 
5.3%
2 38038
 
4.5%
8 35338
 
4.2%
0 28728
 
3.4%
Latin
ValueCountFrequency (%)
N 2
28.6%
A 1
14.3%
I 1
14.3%
C 1
14.3%
U 1
14.3%
S 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 836577
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 252234
30.2%
3 151203
18.1%
4 98895
 
11.8%
5 86240
 
10.3%
9 54103
 
6.5%
6 47615
 
5.7%
7 44176
 
5.3%
2 38038
 
4.5%
8 35338
 
4.2%
0 28728
 
3.4%
Other values (6) 7
 
< 0.1%
Distinct4620
Distinct (%)2.0%
Missing68
Missing (%)< 0.1%
Memory size15.1 MiB
2023-09-22T21:41:18.732218image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length34
Median length29
Mean length10.309434
Min length1

Characters and Unicode

Total characters2429047
Distinct characters36
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique589 ?
Unique (%)0.2%

Sample

1st rowALEM PARAIBA
2nd rowVOLTA REDONDA
3rd rowJAU
4th rowADAMANTINA
5th rowCAMPINAS
ValueCountFrequency (%)
sao 29471
 
7.6%
paulo 17071
 
4.4%
do 13795
 
3.6%
de 12904
 
3.3%
rio 11445
 
3.0%
horizonte 6494
 
1.7%
belo 6323
 
1.6%
janeiro 6253
 
1.6%
fortaleza 5785
 
1.5%
campinas 4953
 
1.3%
Other values (3618) 272780
70.4%
2023-09-22T21:41:19.297360image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 430078
17.7%
O 261821
10.8%
R 180745
 
7.4%
I 178858
 
7.4%
E 153467
 
6.3%
151660
 
6.2%
S 138799
 
5.7%
N 120929
 
5.0%
L 98913
 
4.1%
U 98225
 
4.0%
Other values (26) 615552
25.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 2275123
93.7%
Space Separator 151660
 
6.2%
Dash Punctuation 1178
 
< 0.1%
Other Punctuation 1077
 
< 0.1%
Decimal Number 9
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 430078
18.9%
O 261821
11.5%
R 180745
 
7.9%
I 178858
 
7.9%
E 153467
 
6.7%
S 138799
 
6.1%
N 120929
 
5.3%
L 98913
 
4.3%
U 98225
 
4.3%
T 92314
 
4.1%
Other values (16) 520974
22.9%
Decimal Number
ValueCountFrequency (%)
2 2
22.2%
1 2
22.2%
0 2
22.2%
5 1
11.1%
3 1
11.1%
9 1
11.1%
Other Punctuation
ValueCountFrequency (%)
' 996
92.5%
/ 81
 
7.5%
Space Separator
ValueCountFrequency (%)
151660
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1178
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2275123
93.7%
Common 153924
 
6.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 430078
18.9%
O 261821
11.5%
R 180745
 
7.9%
I 178858
 
7.9%
E 153467
 
6.7%
S 138799
 
6.1%
N 120929
 
5.3%
L 98913
 
4.3%
U 98225
 
4.3%
T 92314
 
4.1%
Other values (16) 520974
22.9%
Common
ValueCountFrequency (%)
151660
98.5%
- 1178
 
0.8%
' 996
 
0.6%
/ 81
 
0.1%
2 2
 
< 0.1%
1 2
 
< 0.1%
0 2
 
< 0.1%
5 1
 
< 0.1%
3 1
 
< 0.1%
9 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2429047
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 430078
17.7%
O 261821
10.8%
R 180745
 
7.4%
I 178858
 
7.4%
E 153467
 
6.3%
151660
 
6.2%
S 138799
 
5.7%
N 120929
 
5.0%
L 98913
 
4.1%
U 98225
 
4.0%
Other values (26) 615552
25.3%

CO_MUN_RES
Real number (ℝ)

HIGH CORRELATION 

Distinct4857
Distinct (%)2.1%
Missing67
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean345654.65
Minimum1
Maximum539934
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 MiB
2023-09-22T21:41:19.506876image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile150740
Q1310175
median352210
Q3410940
95-th percentile520870
Maximum539934
Range539933
Interquartile range (IQR)100765

Descriptive statistics

Standard deviation93463.646
Coefficient of variation (CV)0.27039604
Kurtosis0.20888855
Mean345654.65
Median Absolute Deviation (MAD)58730
Skewness-0.17961232
Sum8.1441419 × 1010
Variance8.7354531 × 109
MonotonicityNot monotonic
2023-09-22T21:41:19.714921image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
355030 16956
 
7.2%
330455 6253
 
2.7%
310620 6139
 
2.6%
230440 5772
 
2.4%
350950 4948
 
2.1%
410690 3791
 
1.6%
292740 3243
 
1.4%
351880 2922
 
1.2%
500270 2770
 
1.2%
261160 2668
 
1.1%
Other values (4847) 180153
76.4%
ValueCountFrequency (%)
1 2
 
< 0.1%
2 3
 
< 0.1%
110001 3
 
< 0.1%
110002 127
0.1%
110003 3
 
< 0.1%
110004 53
< 0.1%
110005 1
 
< 0.1%
110006 5
 
< 0.1%
110007 4
 
< 0.1%
110008 3
 
< 0.1%
ValueCountFrequency (%)
539934 190
0.1%
539933 1
 
< 0.1%
539931 81
 
< 0.1%
539930 81
 
< 0.1%
539929 56
 
< 0.1%
539928 340
0.1%
539925 25
 
< 0.1%
539922 103
 
< 0.1%
539917 83
 
< 0.1%
539913 70
 
< 0.1%

CS_ZONA
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct5
Distinct (%)< 0.1%
Missing20515
Missing (%)8.7%
Memory size12.7 MiB
1
196230 
2
 
13248
9
 
3276
3
 
2412
27/04/2023
 
1

Length

Max length10
Median length1
Mean length1.0000418
Min length1

Characters and Unicode

Total characters215176
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 196230
83.3%
2 13248
 
5.6%
9 3276
 
1.4%
3 2412
 
1.0%
27/04/2023 1
 
< 0.1%
(Missing) 20515
 
8.7%

Length

2023-09-22T21:41:19.890316image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:20.058545image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1 196230
91.2%
2 13248
 
6.2%
9 3276
 
1.5%
3 2412
 
1.1%
27/04/2023 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
1 196230
91.2%
2 13251
 
6.2%
9 3276
 
1.5%
3 2413
 
1.1%
/ 2
 
< 0.1%
0 2
 
< 0.1%
7 1
 
< 0.1%
4 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 215174
> 99.9%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 196230
91.2%
2 13251
 
6.2%
9 3276
 
1.5%
3 2413
 
1.1%
0 2
 
< 0.1%
7 1
 
< 0.1%
4 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
/ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 215176
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 196230
91.2%
2 13251
 
6.2%
9 3276
 
1.5%
3 2413
 
1.1%
/ 2
 
< 0.1%
0 2
 
< 0.1%
7 1
 
< 0.1%
4 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 215176
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 196230
91.2%
2 13251
 
6.2%
9 3276
 
1.5%
3 2413
 
1.1%
/ 2
 
< 0.1%
0 2
 
< 0.1%
7 1
 
< 0.1%
4 1
 
< 0.1%

SURTO_SG
Categorical

HIGH CORRELATION  MISSING 

Distinct3
Distinct (%)60.0%
Missing235677
Missing (%)> 99.9%
Memory size9.0 MiB
2.0
9.0
1.0

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters15
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)40.0%

Sample

1st row9.0
2nd row2.0
3rd row1.0
4th row2.0
5th row2.0

Common Values

ValueCountFrequency (%)
2.0 3
 
< 0.1%
9.0 1
 
< 0.1%
1.0 1
 
< 0.1%
(Missing) 235677
> 99.9%

Length

2023-09-22T21:41:20.215255image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:20.373989image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
2.0 3
60.0%
9.0 1
 
20.0%
1.0 1
 
20.0%

Most occurring characters

ValueCountFrequency (%)
. 5
33.3%
0 5
33.3%
2 3
20.0%
9 1
 
6.7%
1 1
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10
66.7%
Other Punctuation 5
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5
50.0%
2 3
30.0%
9 1
 
10.0%
1 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
. 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 5
33.3%
0 5
33.3%
2 3
20.0%
9 1
 
6.7%
1 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 5
33.3%
0 5
33.3%
2 3
20.0%
9 1
 
6.7%
1 1
 
6.7%

NOSOCOMIAL
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct3
Distinct (%)< 0.1%
Missing28463
Missing (%)12.1%
Memory size12.9 MiB
2.0
192602 
9.0
 
8804
1.0
 
5813

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters621657
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2.0
2nd row2.0
3rd row2.0
4th row2.0
5th row2.0

Common Values

ValueCountFrequency (%)
2.0 192602
81.7%
9.0 8804
 
3.7%
1.0 5813
 
2.5%
(Missing) 28463
 
12.1%

Length

2023-09-22T21:41:20.512351image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:20.674148image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
2.0 192602
92.9%
9.0 8804
 
4.2%
1.0 5813
 
2.8%

Most occurring characters

ValueCountFrequency (%)
. 207219
33.3%
0 207219
33.3%
2 192602
31.0%
9 8804
 
1.4%
1 5813
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 414438
66.7%
Other Punctuation 207219
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 207219
50.0%
2 192602
46.5%
9 8804
 
2.1%
1 5813
 
1.4%
Other Punctuation
ValueCountFrequency (%)
. 207219
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 621657
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 207219
33.3%
0 207219
33.3%
2 192602
31.0%
9 8804
 
1.4%
1 5813
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 621657
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 207219
33.3%
0 207219
33.3%
2 192602
31.0%
9 8804
 
1.4%
1 5813
 
0.9%

AVE_SUINO
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct4
Distinct (%)< 0.1%
Missing37461
Missing (%)15.9%
Memory size12.8 MiB
2.0
165471 
9.0
30464 
1.0
 
1195
3.0
 
1091

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters594663
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2.0
2nd row9.0
3rd row2.0
4th row2.0
5th row2.0

Common Values

ValueCountFrequency (%)
2.0 165471
70.2%
9.0 30464
 
12.9%
1.0 1195
 
0.5%
3.0 1091
 
0.5%
(Missing) 37461
 
15.9%

Length

2023-09-22T21:41:20.816013image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:20.981186image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
2.0 165471
83.5%
9.0 30464
 
15.4%
1.0 1195
 
0.6%
3.0 1091
 
0.6%

Most occurring characters

ValueCountFrequency (%)
. 198221
33.3%
0 198221
33.3%
2 165471
27.8%
9 30464
 
5.1%
1 1195
 
0.2%
3 1091
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 396442
66.7%
Other Punctuation 198221
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 198221
50.0%
2 165471
41.7%
9 30464
 
7.7%
1 1195
 
0.3%
3 1091
 
0.3%
Other Punctuation
ValueCountFrequency (%)
. 198221
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 594663
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 198221
33.3%
0 198221
33.3%
2 165471
27.8%
9 30464
 
5.1%
1 1195
 
0.2%
3 1091
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 594663
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 198221
33.3%
0 198221
33.3%
2 165471
27.8%
9 30464
 
5.1%
1 1195
 
0.2%
3 1091
 
0.2%

FEBRE
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct5
Distinct (%)< 0.1%
Missing33498
Missing (%)14.2%
Memory size12.5 MiB
1
133697 
2
67013 
9
 
1472
14/05/2023
 
1
INAPETENCIA
 
1

Length

Max length11
Median length1
Mean length1.000094
Min length1

Characters and Unicode

Total characters202203
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row1
3rd row2
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 133697
56.7%
2 67013
28.4%
9 1472
 
0.6%
14/05/2023 1
 
< 0.1%
INAPETENCIA 1
 
< 0.1%
(Missing) 33498
 
14.2%

Length

2023-09-22T21:41:21.130081image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:21.306597image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1 133697
66.1%
2 67013
33.1%
9 1472
 
0.7%
14/05/2023 1
 
< 0.1%
inapetencia 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
1 133698
66.1%
2 67015
33.1%
9 1472
 
0.7%
/ 2
 
< 0.1%
0 2
 
< 0.1%
I 2
 
< 0.1%
N 2
 
< 0.1%
A 2
 
< 0.1%
E 2
 
< 0.1%
4 1
 
< 0.1%
Other values (5) 5
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 202190
> 99.9%
Uppercase Letter 11
 
< 0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 133698
66.1%
2 67015
33.1%
9 1472
 
0.7%
0 2
 
< 0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
3 1
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
I 2
18.2%
N 2
18.2%
A 2
18.2%
E 2
18.2%
P 1
9.1%
T 1
9.1%
C 1
9.1%
Other Punctuation
ValueCountFrequency (%)
/ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 202192
> 99.9%
Latin 11
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 133698
66.1%
2 67015
33.1%
9 1472
 
0.7%
/ 2
 
< 0.1%
0 2
 
< 0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
3 1
 
< 0.1%
Latin
ValueCountFrequency (%)
I 2
18.2%
N 2
18.2%
A 2
18.2%
E 2
18.2%
P 1
9.1%
T 1
9.1%
C 1
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 202203
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 133698
66.1%
2 67015
33.1%
9 1472
 
0.7%
/ 2
 
< 0.1%
0 2
 
< 0.1%
I 2
 
< 0.1%
N 2
 
< 0.1%
A 2
 
< 0.1%
E 2
 
< 0.1%
4 1
 
< 0.1%
Other values (5) 5
 
< 0.1%

TOSSE
Categorical

IMBALANCE  MISSING 

Distinct3
Distinct (%)< 0.1%
Missing21043
Missing (%)8.9%
Memory size13.1 MiB
1.0
178631 
2.0
34972 
9.0
 
1036

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters643917
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row9.0
3rd row1.0
4th row2.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 178631
75.8%
2.0 34972
 
14.8%
9.0 1036
 
0.4%
(Missing) 21043
 
8.9%

Length

2023-09-22T21:41:21.471572image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:21.643094image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1.0 178631
83.2%
2.0 34972
 
16.3%
9.0 1036
 
0.5%

Most occurring characters

ValueCountFrequency (%)
. 214639
33.3%
0 214639
33.3%
1 178631
27.7%
2 34972
 
5.4%
9 1036
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 429278
66.7%
Other Punctuation 214639
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 214639
50.0%
1 178631
41.6%
2 34972
 
8.1%
9 1036
 
0.2%
Other Punctuation
ValueCountFrequency (%)
. 214639
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 643917
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 214639
33.3%
0 214639
33.3%
1 178631
27.7%
2 34972
 
5.4%
9 1036
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 643917
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 214639
33.3%
0 214639
33.3%
1 178631
27.7%
2 34972
 
5.4%
9 1036
 
0.2%

GARGANTA
Categorical

HIGH CORRELATION  MISSING 

Distinct3
Distinct (%)< 0.1%
Missing66356
Missing (%)28.2%
Memory size12.2 MiB
2.0
138555 
1.0
25615 
9.0
 
5156

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters507978
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2.0
2nd row9.0
3rd row2.0
4th row2.0
5th row2.0

Common Values

ValueCountFrequency (%)
2.0 138555
58.8%
1.0 25615
 
10.9%
9.0 5156
 
2.2%
(Missing) 66356
28.2%

Length

2023-09-22T21:41:21.805148image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:21.981020image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
2.0 138555
81.8%
1.0 25615
 
15.1%
9.0 5156
 
3.0%

Most occurring characters

ValueCountFrequency (%)
. 169326
33.3%
0 169326
33.3%
2 138555
27.3%
1 25615
 
5.0%
9 5156
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 338652
66.7%
Other Punctuation 169326
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 169326
50.0%
2 138555
40.9%
1 25615
 
7.6%
9 5156
 
1.5%
Other Punctuation
ValueCountFrequency (%)
. 169326
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 507978
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 169326
33.3%
0 169326
33.3%
2 138555
27.3%
1 25615
 
5.0%
9 5156
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 507978
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 169326
33.3%
0 169326
33.3%
2 138555
27.3%
1 25615
 
5.0%
9 5156
 
1.0%

DISPNEIA
Categorical

HIGH CORRELATION  MISSING 

Distinct3
Distinct (%)< 0.1%
Missing31169
Missing (%)13.2%
Memory size12.9 MiB
1.0
152788 
2.0
50381 
9.0
 
1344

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters613539
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row9.0
3rd row1.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 152788
64.8%
2.0 50381
 
21.4%
9.0 1344
 
0.6%
(Missing) 31169
 
13.2%

Length

2023-09-22T21:41:22.126564image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:22.294000image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1.0 152788
74.7%
2.0 50381
 
24.6%
9.0 1344
 
0.7%

Most occurring characters

ValueCountFrequency (%)
. 204513
33.3%
0 204513
33.3%
1 152788
24.9%
2 50381
 
8.2%
9 1344
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 409026
66.7%
Other Punctuation 204513
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 204513
50.0%
1 152788
37.4%
2 50381
 
12.3%
9 1344
 
0.3%
Other Punctuation
ValueCountFrequency (%)
. 204513
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 613539
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 204513
33.3%
0 204513
33.3%
1 152788
24.9%
2 50381
 
8.2%
9 1344
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 613539
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 204513
33.3%
0 204513
33.3%
1 152788
24.9%
2 50381
 
8.2%
9 1344
 
0.2%

DESC_RESP
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct4
Distinct (%)< 0.1%
Missing38572
Missing (%)16.4%
Memory size12.4 MiB
1
143976 
2
51927 
9
 
1206
16/06/2023
 
1

Length

Max length10
Median length1
Mean length1.0000457
Min length1

Characters and Unicode

Total characters197119
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row9
3rd row2
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 143976
61.1%
2 51927
 
22.0%
9 1206
 
0.5%
16/06/2023 1
 
< 0.1%
(Missing) 38572
 
16.4%

Length

2023-09-22T21:41:22.445419image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:22.622097image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1 143976
73.0%
2 51927
 
26.3%
9 1206
 
0.6%
16/06/2023 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
1 143977
73.0%
2 51929
 
26.3%
9 1206
 
0.6%
6 2
 
< 0.1%
/ 2
 
< 0.1%
0 2
 
< 0.1%
3 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 197117
> 99.9%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 143977
73.0%
2 51929
 
26.3%
9 1206
 
0.6%
6 2
 
< 0.1%
0 2
 
< 0.1%
3 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
/ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 197119
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 143977
73.0%
2 51929
 
26.3%
9 1206
 
0.6%
6 2
 
< 0.1%
/ 2
 
< 0.1%
0 2
 
< 0.1%
3 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 197119
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 143977
73.0%
2 51929
 
26.3%
9 1206
 
0.6%
6 2
 
< 0.1%
/ 2
 
< 0.1%
0 2
 
< 0.1%
3 1
 
< 0.1%

SATURACAO
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct5
Distinct (%)< 0.1%
Missing43417
Missing (%)18.4%
Memory size12.7 MiB
1.0
124488 
2.0
66084 
9.0
 
1691
6.0
 
1
0.0
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters576795
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row1.0
2nd row9.0
3rd row1.0
4th row1.0
5th row2.0

Common Values

ValueCountFrequency (%)
1.0 124488
52.8%
2.0 66084
28.0%
9.0 1691
 
0.7%
6.0 1
 
< 0.1%
0.0 1
 
< 0.1%
(Missing) 43417
 
18.4%

Length

2023-09-22T21:41:22.767311image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:22.944026image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1.0 124488
64.7%
2.0 66084
34.4%
9.0 1691
 
0.9%
6.0 1
 
< 0.1%
0.0 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 192266
33.3%
. 192265
33.3%
1 124488
21.6%
2 66084
 
11.5%
9 1691
 
0.3%
6 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 384530
66.7%
Other Punctuation 192265
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 192266
50.0%
1 124488
32.4%
2 66084
 
17.2%
9 1691
 
0.4%
6 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 192265
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 576795
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 192266
33.3%
. 192265
33.3%
1 124488
21.6%
2 66084
 
11.5%
9 1691
 
0.3%
6 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 576795
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 192266
33.3%
. 192265
33.3%
1 124488
21.6%
2 66084
 
11.5%
9 1691
 
0.3%
6 1
 
< 0.1%

DIARREIA
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct3
Distinct (%)< 0.1%
Missing67690
Missing (%)28.7%
Memory size12.2 MiB
2.0
148190 
1.0
17643 
9.0
 
2159

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters503976
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2.0
2nd row9.0
3rd row2.0
4th row2.0
5th row2.0

Common Values

ValueCountFrequency (%)
2.0 148190
62.9%
1.0 17643
 
7.5%
9.0 2159
 
0.9%
(Missing) 67690
28.7%

Length

2023-09-22T21:41:23.105943image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:23.280101image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
2.0 148190
88.2%
1.0 17643
 
10.5%
9.0 2159
 
1.3%

Most occurring characters

ValueCountFrequency (%)
. 167992
33.3%
0 167992
33.3%
2 148190
29.4%
1 17643
 
3.5%
9 2159
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 335984
66.7%
Other Punctuation 167992
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 167992
50.0%
2 148190
44.1%
1 17643
 
5.3%
9 2159
 
0.6%
Other Punctuation
ValueCountFrequency (%)
. 167992
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 503976
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 167992
33.3%
0 167992
33.3%
2 148190
29.4%
1 17643
 
3.5%
9 2159
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 503976
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 167992
33.3%
0 167992
33.3%
2 148190
29.4%
1 17643
 
3.5%
9 2159
 
0.4%

VOMITO
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct4
Distinct (%)< 0.1%
Missing65811
Missing (%)27.9%
Memory size12.2 MiB
2.0
141297 
1.0
26417 
9.0
 
2156
4.0
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters509613
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row1.0
2nd row9.0
3rd row2.0
4th row2.0
5th row2.0

Common Values

ValueCountFrequency (%)
2.0 141297
60.0%
1.0 26417
 
11.2%
9.0 2156
 
0.9%
4.0 1
 
< 0.1%
(Missing) 65811
27.9%

Length

2023-09-22T21:41:23.442502image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:23.642482image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
2.0 141297
83.2%
1.0 26417
 
15.6%
9.0 2156
 
1.3%
4.0 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
. 169871
33.3%
0 169871
33.3%
2 141297
27.7%
1 26417
 
5.2%
9 2156
 
0.4%
4 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 339742
66.7%
Other Punctuation 169871
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 169871
50.0%
2 141297
41.6%
1 26417
 
7.8%
9 2156
 
0.6%
4 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 169871
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 509613
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 169871
33.3%
0 169871
33.3%
2 141297
27.7%
1 26417
 
5.2%
9 2156
 
0.4%
4 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 509613
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 169871
33.3%
0 169871
33.3%
2 141297
27.7%
1 26417
 
5.2%
9 2156
 
0.4%
4 1
 
< 0.1%

OUTRO_SIN
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct6
Distinct (%)< 0.1%
Missing69871
Missing (%)29.6%
Memory size11.8 MiB
2
95193 
1
67406 
9
 
3209
16/06/2023
 
1
16/04/2023"
 
1

Length

Max length12
Median length1
Mean length1.0001809
Min length1

Characters and Unicode

Total characters165841
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row2
2nd row9
3rd row2
4th row1
5th row2

Common Values

ValueCountFrequency (%)
2 95193
40.4%
1 67406
28.6%
9 3209
 
1.4%
16/06/2023 1
 
< 0.1%
16/04/2023" 1
 
< 0.1%
104/06/2023" 1
 
< 0.1%
(Missing) 69871
29.6%

Length

2023-09-22T21:41:23.821142image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:24.010621image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
2 95193
57.4%
1 67406
40.7%
9 3209
 
1.9%
16/06/2023 1
 
< 0.1%
16/04/2023 1
 
< 0.1%
104/06/2023 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
2 95199
57.4%
1 67409
40.6%
9 3209
 
1.9%
0 7
 
< 0.1%
/ 6
 
< 0.1%
6 4
 
< 0.1%
3 3
 
< 0.1%
4 2
 
< 0.1%
" 2
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 165833
> 99.9%
Other Punctuation 8
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 95199
57.4%
1 67409
40.6%
9 3209
 
1.9%
0 7
 
< 0.1%
6 4
 
< 0.1%
3 3
 
< 0.1%
4 2
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
/ 6
75.0%
" 2
 
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 165841
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 95199
57.4%
1 67409
40.6%
9 3209
 
1.9%
0 7
 
< 0.1%
/ 6
 
< 0.1%
6 4
 
< 0.1%
3 3
 
< 0.1%
4 2
 
< 0.1%
" 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 165841
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 95199
57.4%
1 67409
40.6%
9 3209
 
1.9%
0 7
 
< 0.1%
/ 6
 
< 0.1%
6 4
 
< 0.1%
3 3
 
< 0.1%
4 2
 
< 0.1%
" 2
 
< 0.1%

OUTRO_DES
Text

MISSING 

Distinct17752
Distinct (%)26.7%
Missing169256
Missing (%)71.8%
Memory size9.7 MiB
2023-09-22T21:41:24.312107image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length60
Median length54
Mean length14.255743
Min length1

Characters and Unicode

Total characters946952
Distinct characters64
Distinct categories12 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13460 ?
Unique (%)20.3%

Sample

1st rowFRAQUEZA,MAL ESTAR,MIALGIA
2nd rowCORIZA
3rd rowCORIZA
4th rowMIALGIA, CEFALEIA, CALAFRIOS
5th rowLESOES BOLHOSAS+HIPEREMIA
ValueCountFrequency (%)
coriza 22100
 
17.9%
nasal 6264
 
5.1%
dor 4499
 
3.6%
cefaleia 4331
 
3.5%
e 3477
 
2.8%
congestao 3437
 
2.8%
mialgia 3008
 
2.4%
toracica 2044
 
1.7%
de 2033
 
1.6%
inapetencia 1917
 
1.6%
Other values (9046) 70483
57.0%
2023-09-22T21:41:24.879940image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 142413
15.0%
I 95449
10.1%
O 91105
9.6%
C 73217
 
7.7%
R 70439
 
7.4%
E 69973
 
7.4%
57420
 
6.1%
S 55369
 
5.8%
N 46166
 
4.9%
T 37980
 
4.0%
Other values (54) 207421
21.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 859784
90.8%
Space Separator 57433
 
6.1%
Other Punctuation 27202
 
2.9%
Decimal Number 1353
 
0.1%
Math Symbol 922
 
0.1%
Dash Punctuation 164
 
< 0.1%
Open Punctuation 46
 
< 0.1%
Close Punctuation 42
 
< 0.1%
Other Number 2
 
< 0.1%
Other Symbol 2
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 142413
16.6%
I 95449
11.1%
O 91105
10.6%
C 73217
8.5%
R 70439
8.2%
E 69973
8.1%
S 55369
 
6.4%
N 46166
 
5.4%
T 37980
 
4.4%
L 31110
 
3.6%
Other values (16) 146563
17.0%
Other Punctuation
ValueCountFrequency (%)
, 20958
77.0%
. 2396
 
8.8%
/ 2006
 
7.4%
" 944
 
3.5%
; 711
 
2.6%
% 69
 
0.3%
* 49
 
0.2%
? 41
 
0.2%
: 16
 
0.1%
' 7
 
< 0.1%
Other values (2) 5
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
2 227
16.8%
0 183
13.5%
4 171
12.6%
3 163
12.0%
5 144
10.6%
6 126
9.3%
8 121
8.9%
9 80
 
5.9%
1 74
 
5.5%
7 64
 
4.7%
Math Symbol
ValueCountFrequency (%)
+ 908
98.5%
| 5
 
0.5%
< 3
 
0.3%
= 3
 
0.3%
~ 2
 
0.2%
> 1
 
0.1%
Space Separator
ValueCountFrequency (%)
57420
> 99.9%
  13
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 41
97.6%
] 1
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 164
100.0%
Open Punctuation
ValueCountFrequency (%)
( 46
100.0%
Other Number
ValueCountFrequency (%)
² 2
100.0%
Other Symbol
ValueCountFrequency (%)
° 2
100.0%
Modifier Symbol
ValueCountFrequency (%)
^ 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 859784
90.8%
Common 87168
 
9.2%

Most frequent character per script

Common
ValueCountFrequency (%)
57420
65.9%
, 20958
 
24.0%
. 2396
 
2.7%
/ 2006
 
2.3%
" 944
 
1.1%
+ 908
 
1.0%
; 711
 
0.8%
2 227
 
0.3%
0 183
 
0.2%
4 171
 
0.2%
Other values (28) 1244
 
1.4%
Latin
ValueCountFrequency (%)
A 142413
16.6%
I 95449
11.1%
O 91105
10.6%
C 73217
8.5%
R 70439
8.2%
E 69973
8.1%
S 55369
 
6.4%
N 46166
 
5.4%
T 37980
 
4.4%
L 31110
 
3.6%
Other values (16) 146563
17.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 946933
> 99.9%
None 19
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 142413
15.0%
I 95449
10.1%
O 91105
9.6%
C 73217
 
7.7%
R 70439
 
7.4%
E 69973
 
7.4%
57420
 
6.1%
S 55369
 
5.8%
N 46166
 
4.9%
T 37980
 
4.0%
Other values (50) 207402
21.9%
None
ValueCountFrequency (%)
  13
68.4%
² 2
 
10.5%
¿ 2
 
10.5%
° 2
 
10.5%

PUERPERA
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct6
Distinct (%)< 0.1%
Missing170512
Missing (%)72.3%
Memory size10.1 MiB
2
63905 
9
 
719
1
 
543
14/04/2023
 
1
03/05/2021
 
1

Length

Max length10
Median length1
Mean length1.0004143
Min length1

Characters and Unicode

Total characters65197
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 63905
 
27.1%
9 719
 
0.3%
1 543
 
0.2%
14/04/2023 1
 
< 0.1%
03/05/2021 1
 
< 0.1%
04/06/2023 1
 
< 0.1%
(Missing) 170512
72.3%

Length

2023-09-22T21:41:25.069550image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:25.245110image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
2 63905
98.1%
9 719
 
1.1%
1 543
 
0.8%
14/04/2023 1
 
< 0.1%
03/05/2021 1
 
< 0.1%
04/06/2023 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
2 63911
98.0%
9 719
 
1.1%
1 545
 
0.8%
0 8
 
< 0.1%
/ 6
 
< 0.1%
4 3
 
< 0.1%
3 3
 
< 0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65191
> 99.9%
Other Punctuation 6
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 63911
98.0%
9 719
 
1.1%
1 545
 
0.8%
0 8
 
< 0.1%
4 3
 
< 0.1%
3 3
 
< 0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
/ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 65197
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 63911
98.0%
9 719
 
1.1%
1 545
 
0.8%
0 8
 
< 0.1%
/ 6
 
< 0.1%
4 3
 
< 0.1%
3 3
 
< 0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 65197
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 63911
98.0%
9 719
 
1.1%
1 545
 
0.8%
0 8
 
< 0.1%
/ 6
 
< 0.1%
4 3
 
< 0.1%
3 3
 
< 0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%

FATOR_RISC
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct7
Distinct (%)< 0.1%
Missing11
Missing (%)< 0.1%
Memory size13.0 MiB
2
134667 
1
100999 
9
 
1
22/03/2023
 
1
0
 
1
Other values (2)
 
2

Length

Max length10
Median length1
Mean length1.0000806
Min length1

Characters and Unicode

Total characters235690
Distinct characters9
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row1
3rd row1
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 134667
57.1%
1 100999
42.9%
9 1
 
< 0.1%
22/03/2023 1
 
< 0.1%
0 1
 
< 0.1%
27/07/2021 1
 
< 0.1%
AP 1
 
< 0.1%
(Missing) 11
 
< 0.1%

Length

2023-09-22T21:41:25.398716image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:25.591466image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
2 134667
57.1%
1 100999
42.9%
9 1
 
< 0.1%
22/03/2023 1
 
< 0.1%
0 1
 
< 0.1%
27/07/2021 1
 
< 0.1%
ap 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
2 134674
57.1%
1 101000
42.9%
0 5
 
< 0.1%
/ 4
 
< 0.1%
3 2
 
< 0.1%
7 2
 
< 0.1%
9 1
 
< 0.1%
A 1
 
< 0.1%
P 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 235684
> 99.9%
Other Punctuation 4
 
< 0.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 134674
57.1%
1 101000
42.9%
0 5
 
< 0.1%
3 2
 
< 0.1%
7 2
 
< 0.1%
9 1
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
A 1
50.0%
P 1
50.0%
Other Punctuation
ValueCountFrequency (%)
/ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 235688
> 99.9%
Latin 2
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
2 134674
57.1%
1 101000
42.9%
0 5
 
< 0.1%
/ 4
 
< 0.1%
3 2
 
< 0.1%
7 2
 
< 0.1%
9 1
 
< 0.1%
Latin
ValueCountFrequency (%)
A 1
50.0%
P 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 235690
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 134674
57.1%
1 101000
42.9%
0 5
 
< 0.1%
/ 4
 
< 0.1%
3 2
 
< 0.1%
7 2
 
< 0.1%
9 1
 
< 0.1%
A 1
 
< 0.1%
P 1
 
< 0.1%

CARDIOPATI
Categorical

HIGH CORRELATION  MISSING 

Distinct4
Distinct (%)< 0.1%
Missing158886
Missing (%)67.4%
Memory size10.3 MiB
2
39437 
1
36747 
9
 
611
25/03/2023
 
1

Length

Max length10
Median length1
Mean length1.0001172
Min length1

Characters and Unicode

Total characters76805
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row9
3rd row1
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 39437
 
16.7%
1 36747
 
15.6%
9 611
 
0.3%
25/03/2023 1
 
< 0.1%
(Missing) 158886
67.4%

Length

2023-09-22T21:41:25.757630image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:25.940795image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
2 39437
51.4%
1 36747
47.9%
9 611
 
0.8%
25/03/2023 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
2 39440
51.4%
1 36747
47.8%
9 611
 
0.8%
/ 2
 
< 0.1%
0 2
 
< 0.1%
3 2
 
< 0.1%
5 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 76803
> 99.9%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 39440
51.4%
1 36747
47.8%
9 611
 
0.8%
0 2
 
< 0.1%
3 2
 
< 0.1%
5 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
/ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 76805
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 39440
51.4%
1 36747
47.8%
9 611
 
0.8%
/ 2
 
< 0.1%
0 2
 
< 0.1%
3 2
 
< 0.1%
5 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 76805
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 39440
51.4%
1 36747
47.8%
9 611
 
0.8%
/ 2
 
< 0.1%
0 2
 
< 0.1%
3 2
 
< 0.1%
5 1
 
< 0.1%

HEMATOLOGI
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct5
Distinct (%)< 0.1%
Missing169537
Missing (%)71.9%
Memory size10.1 MiB
2
63187 
1
 
2125
9
 
831
24/02/2023
 
1
85 - COVID-19 ASTRAZENECA/FIOCRUZ - COVISHIELD
 
1

Length

Max length46
Median length1
Mean length1.0008164
Min length1

Characters and Unicode

Total characters66199
Distinct characters27
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row2
2nd row9
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 63187
 
26.8%
1 2125
 
0.9%
9 831
 
0.4%
24/02/2023 1
 
< 0.1%
85 - COVID-19 ASTRAZENECA/FIOCRUZ - COVISHIELD 1
 
< 0.1%
(Missing) 169537
71.9%

Length

2023-09-22T21:41:26.091056image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:26.270610image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
2 63187
95.5%
1 2125
 
3.2%
9 831
 
1.3%
2
 
< 0.1%
24/02/2023 1
 
< 0.1%
85 1
 
< 0.1%
covid-19 1
 
< 0.1%
astrazeneca/fiocruz 1
 
< 0.1%
covishield 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
2 63191
95.5%
1 2126
 
3.2%
9 832
 
1.3%
5
 
< 0.1%
C 4
 
< 0.1%
I 4
 
< 0.1%
E 3
 
< 0.1%
/ 3
 
< 0.1%
A 3
 
< 0.1%
- 3
 
< 0.1%
Other values (17) 25
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66155
99.9%
Uppercase Letter 33
 
< 0.1%
Space Separator 5
 
< 0.1%
Other Punctuation 3
 
< 0.1%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 4
12.1%
I 4
12.1%
E 3
9.1%
A 3
9.1%
O 3
9.1%
D 2
 
6.1%
Z 2
 
6.1%
R 2
 
6.1%
S 2
 
6.1%
V 2
 
6.1%
Other values (6) 6
18.2%
Decimal Number
ValueCountFrequency (%)
2 63191
95.5%
1 2126
 
3.2%
9 832
 
1.3%
0 2
 
< 0.1%
5 1
 
< 0.1%
8 1
 
< 0.1%
3 1
 
< 0.1%
4 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
5
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 66166
> 99.9%
Latin 33
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
C 4
12.1%
I 4
12.1%
E 3
9.1%
A 3
9.1%
O 3
9.1%
D 2
 
6.1%
Z 2
 
6.1%
R 2
 
6.1%
S 2
 
6.1%
V 2
 
6.1%
Other values (6) 6
18.2%
Common
ValueCountFrequency (%)
2 63191
95.5%
1 2126
 
3.2%
9 832
 
1.3%
5
 
< 0.1%
/ 3
 
< 0.1%
- 3
 
< 0.1%
0 2
 
< 0.1%
5 1
 
< 0.1%
8 1
 
< 0.1%
3 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 66199
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 63191
95.5%
1 2126
 
3.2%
9 832
 
1.3%
5
 
< 0.1%
C 4
 
< 0.1%
I 4
 
< 0.1%
E 3
 
< 0.1%
/ 3
 
< 0.1%
A 3
 
< 0.1%
- 3
 
< 0.1%
Other values (17) 25
 
< 0.1%

SIND_DOWN
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct6
Distinct (%)< 0.1%
Missing169741
Missing (%)72.0%
Memory size10.1 MiB
2
63616 
1
 
1607
9
 
715
0
 
1
85 - COVID-19 ASTRAZENECA/FIOCRUZ - COVISHIELD
 
1

Length

Max length46
Median length1
Mean length1.0007583
Min length1

Characters and Unicode

Total characters65991
Distinct characters27
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row2
2nd row9
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 63616
 
27.0%
1 1607
 
0.7%
9 715
 
0.3%
0 1
 
< 0.1%
85 - COVID-19 ASTRAZENECA/FIOCRUZ - COVISHIELD 1
 
< 0.1%
MACAPA 1
 
< 0.1%
(Missing) 169741
72.0%

Length

2023-09-22T21:41:26.426733image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:27.420892image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
2 63616
96.5%
1 1607
 
2.4%
9 715
 
1.1%
2
 
< 0.1%
0 1
 
< 0.1%
85 1
 
< 0.1%
covid-19 1
 
< 0.1%
astrazeneca/fiocruz 1
 
< 0.1%
covishield 1
 
< 0.1%
macapa 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
2 63616
96.4%
1 1608
 
2.4%
9 716
 
1.1%
A 6
 
< 0.1%
5
 
< 0.1%
C 5
 
< 0.1%
I 4
 
< 0.1%
- 3
 
< 0.1%
O 3
 
< 0.1%
E 3
 
< 0.1%
Other values (17) 22
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65943
99.9%
Uppercase Letter 39
 
0.1%
Space Separator 5
 
< 0.1%
Dash Punctuation 3
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 6
15.4%
C 5
12.8%
I 4
10.3%
O 3
 
7.7%
E 3
 
7.7%
D 2
 
5.1%
R 2
 
5.1%
V 2
 
5.1%
S 2
 
5.1%
Z 2
 
5.1%
Other values (8) 8
20.5%
Decimal Number
ValueCountFrequency (%)
2 63616
96.5%
1 1608
 
2.4%
9 716
 
1.1%
8 1
 
< 0.1%
5 1
 
< 0.1%
0 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 65952
99.9%
Latin 39
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 6
15.4%
C 5
12.8%
I 4
10.3%
O 3
 
7.7%
E 3
 
7.7%
D 2
 
5.1%
R 2
 
5.1%
V 2
 
5.1%
S 2
 
5.1%
Z 2
 
5.1%
Other values (8) 8
20.5%
Common
ValueCountFrequency (%)
2 63616
96.5%
1 1608
 
2.4%
9 716
 
1.1%
5
 
< 0.1%
- 3
 
< 0.1%
8 1
 
< 0.1%
/ 1
 
< 0.1%
5 1
 
< 0.1%
0 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 65991
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 63616
96.4%
1 1608
 
2.4%
9 716
 
1.1%
A 6
 
< 0.1%
5
 
< 0.1%
C 5
 
< 0.1%
I 4
 
< 0.1%
- 3
 
< 0.1%
O 3
 
< 0.1%
E 3
 
< 0.1%
Other values (17) 22
 
< 0.1%

HEPATICA
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct4
Distinct (%)< 0.1%
Missing169908
Missing (%)72.1%
Memory size10.2 MiB
2.0
63435 
1.0
 
1521
9.0
 
817
160030.0
 
1

Length

Max length8
Median length3
Mean length3.000076
Min length3

Characters and Unicode

Total characters197327
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row2.0
2nd row9.0
3rd row2.0
4th row2.0
5th row2.0

Common Values

ValueCountFrequency (%)
2.0 63435
 
26.9%
1.0 1521
 
0.6%
9.0 817
 
0.3%
160030.0 1
 
< 0.1%
(Missing) 169908
72.1%

Length

2023-09-22T21:41:27.804417image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:28.173074image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
2.0 63435
96.4%
1.0 1521
 
2.3%
9.0 817
 
1.2%
160030.0 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 65777
33.3%
. 65774
33.3%
2 63435
32.1%
1 1522
 
0.8%
9 817
 
0.4%
6 1
 
< 0.1%
3 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 131553
66.7%
Other Punctuation 65774
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 65777
50.0%
2 63435
48.2%
1 1522
 
1.2%
9 817
 
0.6%
6 1
 
< 0.1%
3 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 65774
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 197327
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 65777
33.3%
. 65774
33.3%
2 63435
32.1%
1 1522
 
0.8%
9 817
 
0.4%
6 1
 
< 0.1%
3 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 197327
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 65777
33.3%
. 65774
33.3%
2 63435
32.1%
1 1522
 
0.8%
9 817
 
0.4%
6 1
 
< 0.1%
3 1
 
< 0.1%

ASMA
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct5
Distinct (%)< 0.1%
Missing165304
Missing (%)70.1%
Memory size10.2 MiB
2
53847 
1
15802 
9
 
727
NORTE"
 
1
85 - COVID-19 ASTRAZENECA/FIOCRUZ - COVISHIELD
 
1

Length

Max length46
Median length1
Mean length1.0007247
Min length1

Characters and Unicode

Total characters70429
Distinct characters25
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row2
2nd row9
3rd row2
4th row2
5th row1

Common Values

ValueCountFrequency (%)
2 53847
 
22.8%
1 15802
 
6.7%
9 727
 
0.3%
NORTE" 1
 
< 0.1%
85 - COVID-19 ASTRAZENECA/FIOCRUZ - COVISHIELD 1
 
< 0.1%
(Missing) 165304
70.1%

Length

2023-09-22T21:41:28.437210image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:28.759650image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
2 53847
76.5%
1 15802
 
22.5%
9 727
 
1.0%
2
 
< 0.1%
norte 1
 
< 0.1%
85 1
 
< 0.1%
covid-19 1
 
< 0.1%
astrazeneca/fiocruz 1
 
< 0.1%
covishield 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
2 53847
76.5%
1 15803
 
22.4%
9 728
 
1.0%
6
 
< 0.1%
O 4
 
< 0.1%
I 4
 
< 0.1%
C 4
 
< 0.1%
E 4
 
< 0.1%
A 3
 
< 0.1%
- 3
 
< 0.1%
Other values (15) 23
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 70380
99.9%
Uppercase Letter 38
 
0.1%
Space Separator 6
 
< 0.1%
Dash Punctuation 3
 
< 0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
O 4
10.5%
I 4
10.5%
C 4
10.5%
E 4
10.5%
A 3
 
7.9%
R 3
 
7.9%
T 2
 
5.3%
V 2
 
5.3%
D 2
 
5.3%
N 2
 
5.3%
Other values (6) 8
21.1%
Decimal Number
ValueCountFrequency (%)
2 53847
76.5%
1 15803
 
22.5%
9 728
 
1.0%
8 1
 
< 0.1%
5 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
" 1
50.0%
/ 1
50.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 70391
99.9%
Latin 38
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
O 4
10.5%
I 4
10.5%
C 4
10.5%
E 4
10.5%
A 3
 
7.9%
R 3
 
7.9%
T 2
 
5.3%
V 2
 
5.3%
D 2
 
5.3%
N 2
 
5.3%
Other values (6) 8
21.1%
Common
ValueCountFrequency (%)
2 53847
76.5%
1 15803
 
22.5%
9 728
 
1.0%
6
 
< 0.1%
- 3
 
< 0.1%
8 1
 
< 0.1%
5 1
 
< 0.1%
" 1
 
< 0.1%
/ 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70429
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 53847
76.5%
1 15803
 
22.4%
9 728
 
1.0%
6
 
< 0.1%
O 4
 
< 0.1%
I 4
 
< 0.1%
C 4
 
< 0.1%
E 4
 
< 0.1%
A 3
 
< 0.1%
- 3
 
< 0.1%
Other values (15) 23
 
< 0.1%

DIABETES
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct5
Distinct (%)< 0.1%
Missing163162
Missing (%)69.2%
Memory size10.2 MiB
2
49392 
1
22514 
9
 
612
1784
 
1
213VCD031W
 
1

Length

Max length10
Median length1
Mean length1.0001655
Min length1

Characters and Unicode

Total characters72532
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row2
2nd row9
3rd row1
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 49392
 
21.0%
1 22514
 
9.6%
9 612
 
0.3%
1784 1
 
< 0.1%
213VCD031W 1
 
< 0.1%
(Missing) 163162
69.2%

Length

2023-09-22T21:41:29.133891image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:29.435670image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
2 49392
68.1%
1 22514
31.0%
9 612
 
0.8%
1784 1
 
< 0.1%
213vcd031w 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
2 49393
68.1%
1 22517
31.0%
9 612
 
0.8%
3 2
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%
4 1
 
< 0.1%
V 1
 
< 0.1%
C 1
 
< 0.1%
D 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 72528
> 99.9%
Uppercase Letter 4
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 49393
68.1%
1 22517
31.0%
9 612
 
0.8%
3 2
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%
4 1
 
< 0.1%
0 1
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
V 1
25.0%
C 1
25.0%
D 1
25.0%
W 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 72528
> 99.9%
Latin 4
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
2 49393
68.1%
1 22517
31.0%
9 612
 
0.8%
3 2
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%
4 1
 
< 0.1%
0 1
 
< 0.1%
Latin
ValueCountFrequency (%)
V 1
25.0%
C 1
25.0%
D 1
25.0%
W 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 72532
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 49393
68.1%
1 22517
31.0%
9 612
 
0.8%
3 2
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%
4 1
 
< 0.1%
V 1
 
< 0.1%
C 1
 
< 0.1%
D 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

NEUROLOGIC
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct5
Distinct (%)< 0.1%
Missing166870
Missing (%)70.8%
Memory size10.2 MiB
2
57058 
1
11018 
9
 
734
FORMOSA
 
1
216VCD220Z
 
1

Length

Max length10
Median length1
Mean length1.000218
Min length1

Characters and Unicode

Total characters68827
Distinct characters15
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row2
2nd row9
3rd row2
4th row1
5th row2

Common Values

ValueCountFrequency (%)
2 57058
 
24.2%
1 11018
 
4.7%
9 734
 
0.3%
FORMOSA 1
 
< 0.1%
216VCD220Z 1
 
< 0.1%
(Missing) 166870
70.8%

Length

2023-09-22T21:41:29.612981image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:29.800288image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
2 57058
82.9%
1 11018
 
16.0%
9 734
 
1.1%
formosa 1
 
< 0.1%
216vcd220z 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
2 57061
82.9%
1 11019
 
16.0%
9 734
 
1.1%
O 2
 
< 0.1%
F 1
 
< 0.1%
R 1
 
< 0.1%
M 1
 
< 0.1%
S 1
 
< 0.1%
A 1
 
< 0.1%
6 1
 
< 0.1%
Other values (5) 5
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68816
> 99.9%
Uppercase Letter 11
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
O 2
18.2%
F 1
9.1%
R 1
9.1%
M 1
9.1%
S 1
9.1%
A 1
9.1%
V 1
9.1%
C 1
9.1%
D 1
9.1%
Z 1
9.1%
Decimal Number
ValueCountFrequency (%)
2 57061
82.9%
1 11019
 
16.0%
9 734
 
1.1%
6 1
 
< 0.1%
0 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 68816
> 99.9%
Latin 11
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
O 2
18.2%
F 1
9.1%
R 1
9.1%
M 1
9.1%
S 1
9.1%
A 1
9.1%
V 1
9.1%
C 1
9.1%
D 1
9.1%
Z 1
9.1%
Common
ValueCountFrequency (%)
2 57061
82.9%
1 11019
 
16.0%
9 734
 
1.1%
6 1
 
< 0.1%
0 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 68827
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 57061
82.9%
1 11019
 
16.0%
9 734
 
1.1%
O 2
 
< 0.1%
F 1
 
< 0.1%
R 1
 
< 0.1%
M 1
 
< 0.1%
S 1
 
< 0.1%
A 1
 
< 0.1%
6 1
 
< 0.1%
Other values (5) 5
 
< 0.1%

PNEUMOPATI
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED 

Distinct6
Distinct (%)< 0.1%
Missing167022
Missing (%)70.9%
Infinite0
Infinite (%)0.0%
Mean9.5025925
Minimum1
Maximum520800
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 MiB
2023-09-22T21:41:29.940355image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q32
95-th percentile2
Maximum520800
Range520799
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1987.5475
Coefficient of variation (CV)209.15845
Kurtosis68659.974
Mean9.5025925
Median Absolute Deviation (MAD)0
Skewness262.03046
Sum652448
Variance3950345.1
MonotonicityNot monotonic
2023-09-22T21:41:30.091402image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2 56429
 
23.9%
1 11409
 
4.8%
9 819
 
0.3%
520800 1
 
< 0.1%
4 1
 
< 0.1%
6 1
 
< 0.1%
(Missing) 167022
70.9%
ValueCountFrequency (%)
1 11409
 
4.8%
2 56429
23.9%
4 1
 
< 0.1%
6 1
 
< 0.1%
9 819
 
0.3%
520800 1
 
< 0.1%
ValueCountFrequency (%)
520800 1
 
< 0.1%
9 819
 
0.3%
6 1
 
< 0.1%
4 1
 
< 0.1%
2 56429
23.9%
1 11409
 
4.8%

IMUNODEPRE
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct4
Distinct (%)< 0.1%
Missing167973
Missing (%)71.3%
Memory size10.3 MiB
2.0
60305 
1.0
6579 
9.0
 
824
6.0
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters203127
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row2.0
2nd row1.0
3rd row2.0
4th row2.0
5th row2.0

Common Values

ValueCountFrequency (%)
2.0 60305
 
25.6%
1.0 6579
 
2.8%
9.0 824
 
0.3%
6.0 1
 
< 0.1%
(Missing) 167973
71.3%

Length

2023-09-22T21:41:30.255273image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:30.436009image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
2.0 60305
89.1%
1.0 6579
 
9.7%
9.0 824
 
1.2%
6.0 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
. 67709
33.3%
0 67709
33.3%
2 60305
29.7%
1 6579
 
3.2%
9 824
 
0.4%
6 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 135418
66.7%
Other Punctuation 67709
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 67709
50.0%
2 60305
44.5%
1 6579
 
4.9%
9 824
 
0.6%
6 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 67709
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 203127
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 67709
33.3%
0 67709
33.3%
2 60305
29.7%
1 6579
 
3.2%
9 824
 
0.4%
6 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 203127
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 67709
33.3%
0 67709
33.3%
2 60305
29.7%
1 6579
 
3.2%
9 824
 
0.4%
6 1
 
< 0.1%

RENAL
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct4
Distinct (%)< 0.1%
Missing168861
Missing (%)71.6%
Memory size10.1 MiB
2
60322 
1
 
5734
9
 
764
06/02/2023
 
1

Length

Max length10
Median length1
Mean length1.0001347
Min length1

Characters and Unicode

Total characters66830
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row2
2nd row9
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 60322
 
25.6%
1 5734
 
2.4%
9 764
 
0.3%
06/02/2023 1
 
< 0.1%
(Missing) 168861
71.6%

Length

2023-09-22T21:41:30.610271image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:30.799276image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
2 60322
90.3%
1 5734
 
8.6%
9 764
 
1.1%
06/02/2023 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
2 60325
90.3%
1 5734
 
8.6%
9 764
 
1.1%
0 3
 
< 0.1%
/ 2
 
< 0.1%
6 1
 
< 0.1%
3 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66828
> 99.9%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 60325
90.3%
1 5734
 
8.6%
9 764
 
1.1%
0 3
 
< 0.1%
6 1
 
< 0.1%
3 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
/ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 66830
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 60325
90.3%
1 5734
 
8.6%
9 764
 
1.1%
0 3
 
< 0.1%
/ 2
 
< 0.1%
6 1
 
< 0.1%
3 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 66830
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 60325
90.3%
1 5734
 
8.6%
9 764
 
1.1%
0 3
 
< 0.1%
/ 2
 
< 0.1%
6 1
 
< 0.1%
3 1
 
< 0.1%

OBESIDADE
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct4
Distinct (%)< 0.1%
Missing169987
Missing (%)72.1%
Memory size10.1 MiB
2
59664 
1
 
4979
9
 
1051
DISLIPIDEMIA, HP B
 
1

Length

Max length18
Median length1
Mean length1.0002588
Min length1

Characters and Unicode

Total characters65712
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row2
2nd row9
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 59664
 
25.3%
1 4979
 
2.1%
9 1051
 
0.4%
DISLIPIDEMIA, HP B 1
 
< 0.1%
(Missing) 169987
72.1%

Length

2023-09-22T21:41:30.961006image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:31.143422image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
2 59664
90.8%
1 4979
 
7.6%
9 1051
 
1.6%
dislipidemia 1
 
< 0.1%
hp 1
 
< 0.1%
b 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
2 59664
90.8%
1 4979
 
7.6%
9 1051
 
1.6%
I 4
 
< 0.1%
D 2
 
< 0.1%
P 2
 
< 0.1%
2
 
< 0.1%
S 1
 
< 0.1%
L 1
 
< 0.1%
E 1
 
< 0.1%
Other values (5) 5
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65694
> 99.9%
Uppercase Letter 15
 
< 0.1%
Space Separator 2
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
I 4
26.7%
D 2
13.3%
P 2
13.3%
S 1
 
6.7%
L 1
 
6.7%
E 1
 
6.7%
M 1
 
6.7%
A 1
 
6.7%
H 1
 
6.7%
B 1
 
6.7%
Decimal Number
ValueCountFrequency (%)
2 59664
90.8%
1 4979
 
7.6%
9 1051
 
1.6%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 65697
> 99.9%
Latin 15
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
I 4
26.7%
D 2
13.3%
P 2
13.3%
S 1
 
6.7%
L 1
 
6.7%
E 1
 
6.7%
M 1
 
6.7%
A 1
 
6.7%
H 1
 
6.7%
B 1
 
6.7%
Common
ValueCountFrequency (%)
2 59664
90.8%
1 4979
 
7.6%
9 1051
 
1.6%
2
 
< 0.1%
, 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 65712
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 59664
90.8%
1 4979
 
7.6%
9 1051
 
1.6%
I 4
 
< 0.1%
D 2
 
< 0.1%
P 2
 
< 0.1%
2
 
< 0.1%
S 1
 
< 0.1%
L 1
 
< 0.1%
E 1
 
< 0.1%
Other values (5) 5
 
< 0.1%

OBES_IMC
Text

MISSING 

Distinct154
Distinct (%)27.9%
Missing235131
Missing (%)99.8%
Memory size7.2 MiB
2023-09-22T21:41:31.479081image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length4
Mean length2.5553539
Min length1

Characters and Unicode

Total characters1408
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique80 ?
Unique (%)14.5%

Sample

1st row30
2nd row30
3rd row40
4th row18,8
5th row1
ValueCountFrequency (%)
0 101
 
18.3%
30 45
 
8.2%
40 33
 
6.0%
0,1 28
 
5.1%
0,2 24
 
4.4%
35 23
 
4.2%
32 14
 
2.5%
1 12
 
2.2%
31 8
 
1.5%
30,4 7
 
1.3%
Other values (144) 256
46.5%
2023-09-22T21:41:32.027099image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 273
19.4%
0 266
18.9%
, 248
17.6%
4 137
9.7%
2 122
8.7%
1 105
 
7.5%
5 88
 
6.2%
6 44
 
3.1%
8 42
 
3.0%
9 41
 
2.9%
Other values (2) 42
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1158
82.2%
Other Punctuation 250
 
17.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 273
23.6%
0 266
23.0%
4 137
11.8%
2 122
10.5%
1 105
 
9.1%
5 88
 
7.6%
6 44
 
3.8%
8 42
 
3.6%
9 41
 
3.5%
7 40
 
3.5%
Other Punctuation
ValueCountFrequency (%)
, 248
99.2%
/ 2
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
Common 1408
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 273
19.4%
0 266
18.9%
, 248
17.6%
4 137
9.7%
2 122
8.7%
1 105
 
7.5%
5 88
 
6.2%
6 44
 
3.1%
8 42
 
3.0%
9 41
 
2.9%
Other values (2) 42
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1408
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 273
19.4%
0 266
18.9%
, 248
17.6%
4 137
9.7%
2 122
8.7%
1 105
 
7.5%
5 88
 
6.2%
6 44
 
3.1%
8 42
 
3.0%
9 41
 
2.9%
Other values (2) 42
 
3.0%

OUT_MORBI
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct8
Distinct (%)< 0.1%
Missing158647
Missing (%)67.3%
Memory size10.3 MiB
1
43128 
2
33172 
9
 
730
04/08/2023
 
1
29/01/2021
 
1
Other values (3)
 
3

Length

Max length10
Median length1
Mean length1.0004673
Min length1

Characters and Unicode

Total characters77071
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st row9
2nd row2
3rd row2
4th row1
5th row2

Common Values

ValueCountFrequency (%)
1 43128
 
18.3%
2 33172
 
14.1%
9 730
 
0.3%
04/08/2023 1
 
< 0.1%
29/01/2021 1
 
< 0.1%
06/02/2023 1
 
< 0.1%
5 1
 
< 0.1%
04/06/2023 1
 
< 0.1%
(Missing) 158647
67.3%

Length

2023-09-22T21:41:32.217175image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:32.407157image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1 43128
56.0%
2 33172
43.1%
9 730
 
0.9%
04/08/2023 1
 
< 0.1%
29/01/2021 1
 
< 0.1%
06/02/2023 1
 
< 0.1%
5 1
 
< 0.1%
04/06/2023 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
1 43130
56.0%
2 33182
43.1%
9 731
 
0.9%
0 11
 
< 0.1%
/ 8
 
< 0.1%
3 3
 
< 0.1%
4 2
 
< 0.1%
6 2
 
< 0.1%
8 1
 
< 0.1%
5 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 77063
> 99.9%
Other Punctuation 8
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 43130
56.0%
2 33182
43.1%
9 731
 
0.9%
0 11
 
< 0.1%
3 3
 
< 0.1%
4 2
 
< 0.1%
6 2
 
< 0.1%
8 1
 
< 0.1%
5 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
/ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 77071
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 43130
56.0%
2 33182
43.1%
9 731
 
0.9%
0 11
 
< 0.1%
/ 8
 
< 0.1%
3 3
 
< 0.1%
4 2
 
< 0.1%
6 2
 
< 0.1%
8 1
 
< 0.1%
5 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 77071
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 43130
56.0%
2 33182
43.1%
9 731
 
0.9%
0 11
 
< 0.1%
/ 8
 
< 0.1%
3 3
 
< 0.1%
4 2
 
< 0.1%
6 2
 
< 0.1%
8 1
 
< 0.1%
5 1
 
< 0.1%

MORB_DESC
Text

MISSING 

Distinct15141
Distinct (%)35.6%
Missing193125
Missing (%)81.9%
Memory size8.8 MiB
2023-09-22T21:41:32.766730image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length60
Median length26
Mean length14.00329
Min length1

Characters and Unicode

Total characters595938
Distinct characters65
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11677 ?
Unique (%)27.4%

Sample

1st rowELA+TQT EM VM+GTT+ILEOSTOMIA
2nd rowAVC PREVIO
3rd rowAUTISMO
4th rowDLP
5th rowHAS
ValueCountFrequency (%)
has 8966
 
10.5%
de 4263
 
5.0%
dpoc 2430
 
2.8%
ca 1650
 
1.9%
1617
 
1.9%
prematuridade 1089
 
1.3%
hipotireoidismo 1037
 
1.2%
anos 1015
 
1.2%
e 996
 
1.2%
alzheimer 989
 
1.2%
Other values (9008) 61500
71.9%
2023-09-22T21:41:33.330004image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 74602
12.5%
E 55366
 
9.3%
I 54088
 
9.1%
43262
 
7.3%
O 42625
 
7.2%
S 39902
 
6.7%
R 32848
 
5.5%
T 30749
 
5.2%
C 25746
 
4.3%
D 25672
 
4.3%
Other values (55) 171078
28.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 531061
89.1%
Space Separator 43292
 
7.3%
Other Punctuation 14856
 
2.5%
Decimal Number 3825
 
0.6%
Math Symbol 1482
 
0.2%
Dash Punctuation 890
 
0.1%
Open Punctuation 267
 
< 0.1%
Close Punctuation 210
 
< 0.1%
Other Number 26
 
< 0.1%
Other Letter 24
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 74602
14.0%
E 55366
10.4%
I 54088
10.2%
O 42625
 
8.0%
S 39902
 
7.5%
R 32848
 
6.2%
T 30749
 
5.8%
C 25746
 
4.8%
D 25672
 
4.8%
P 23469
 
4.4%
Other values (18) 125994
23.7%
Other Punctuation
ValueCountFrequency (%)
, 9970
67.1%
/ 2346
 
15.8%
. 1426
 
9.6%
; 754
 
5.1%
? 138
 
0.9%
" 96
 
0.6%
* 47
 
0.3%
: 28
 
0.2%
¿ 16
 
0.1%
# 16
 
0.1%
Other values (3) 19
 
0.1%
Decimal Number
ValueCountFrequency (%)
2 1654
43.2%
0 481
 
12.6%
1 431
 
11.3%
3 388
 
10.1%
4 276
 
7.2%
6 191
 
5.0%
5 162
 
4.2%
8 90
 
2.4%
7 80
 
2.1%
9 72
 
1.9%
Math Symbol
ValueCountFrequency (%)
+ 1213
81.8%
< 234
 
15.8%
| 18
 
1.2%
> 14
 
0.9%
= 3
 
0.2%
Space Separator
ValueCountFrequency (%)
43262
99.9%
  30
 
0.1%
Other Letter
ValueCountFrequency (%)
º 23
95.8%
ª 1
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 890
100.0%
Open Punctuation
ValueCountFrequency (%)
( 267
100.0%
Close Punctuation
ValueCountFrequency (%)
) 210
100.0%
Other Number
ValueCountFrequency (%)
² 26
100.0%
Other Symbol
ValueCountFrequency (%)
° 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 531085
89.1%
Common 64853
 
10.9%

Most frequent character per script

Common
ValueCountFrequency (%)
43262
66.7%
, 9970
 
15.4%
/ 2346
 
3.6%
2 1654
 
2.6%
. 1426
 
2.2%
+ 1213
 
1.9%
- 890
 
1.4%
; 754
 
1.2%
0 481
 
0.7%
1 431
 
0.7%
Other values (25) 2426
 
3.7%
Latin
ValueCountFrequency (%)
A 74602
14.0%
E 55366
10.4%
I 54088
10.2%
O 42625
 
8.0%
S 39902
 
7.5%
R 32848
 
6.2%
T 30749
 
5.8%
C 25746
 
4.8%
D 25672
 
4.8%
P 23469
 
4.4%
Other values (20) 126018
23.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 595828
> 99.9%
None 110
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 74602
12.5%
E 55366
 
9.3%
I 54088
 
9.1%
43262
 
7.3%
O 42625
 
7.2%
S 39902
 
6.7%
R 32848
 
5.5%
T 30749
 
5.2%
C 25746
 
4.3%
D 25672
 
4.3%
Other values (47) 170968
28.7%
None
ValueCountFrequency (%)
  30
27.3%
² 26
23.6%
º 23
20.9%
¿ 16
14.5%
Ñ 7
 
6.4%
° 5
 
4.5%
Ö 2
 
1.8%
ª 1
 
0.9%

VACINA
Categorical

HIGH CORRELATION  MISSING 

Distinct5
Distinct (%)< 0.1%
Missing111781
Missing (%)47.4%
Memory size11.1 MiB
9
62219 
2
46974 
1
14706 
0
 
1
28/02/2023
 
1

Length

Max length10
Median length1
Mean length1.0000726
Min length1

Characters and Unicode

Total characters123910
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row9
3rd row2
4th row1
5th row9

Common Values

ValueCountFrequency (%)
9 62219
26.4%
2 46974
19.9%
1 14706
 
6.2%
0 1
 
< 0.1%
28/02/2023 1
 
< 0.1%
(Missing) 111781
47.4%

Length

2023-09-22T21:41:33.524647image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:33.712966image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
9 62219
50.2%
2 46974
37.9%
1 14706
 
11.9%
0 1
 
< 0.1%
28/02/2023 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
9 62219
50.2%
2 46978
37.9%
1 14706
 
11.9%
0 3
 
< 0.1%
/ 2
 
< 0.1%
8 1
 
< 0.1%
3 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 123908
> 99.9%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 62219
50.2%
2 46978
37.9%
1 14706
 
11.9%
0 3
 
< 0.1%
8 1
 
< 0.1%
3 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
/ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 123910
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
9 62219
50.2%
2 46978
37.9%
1 14706
 
11.9%
0 3
 
< 0.1%
/ 2
 
< 0.1%
8 1
 
< 0.1%
3 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 123910
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 62219
50.2%
2 46978
37.9%
1 14706
 
11.9%
0 3
 
< 0.1%
/ 2
 
< 0.1%
8 1
 
< 0.1%
3 1
 
< 0.1%

DT_UT_DOSE
Text

MISSING 

Distinct693
Distinct (%)8.7%
Missing227695
Missing (%)96.6%
Memory size7.5 MiB
2023-09-22T21:41:34.009828image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length42
Median length10
Mean length10.000626
Min length1

Characters and Unicode

Total characters79875
Distinct characters25
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique183 ?
Unique (%)2.3%

Sample

1st row17/05/2022
2nd row13/05/2022
3rd row20/08/2022
4th row10/05/2022
5th row06/04/2022
ValueCountFrequency (%)
15/04/2023 197
 
2.5%
30/04/2022 151
 
1.9%
20/04/2023 149
 
1.9%
18/04/2023 109
 
1.4%
25/04/2023 109
 
1.4%
15/05/2023 108
 
1.4%
17/04/2023 99
 
1.2%
10/04/2023 94
 
1.2%
12/04/2023 92
 
1.2%
05/05/2023 92
 
1.2%
Other values (687) 6792
85.0%
2023-09-22T21:41:34.487868image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 22497
28.2%
0 19188
24.0%
/ 15967
20.0%
3 5932
 
7.4%
1 4371
 
5.5%
5 3598
 
4.5%
4 3478
 
4.4%
6 1721
 
2.2%
7 1184
 
1.5%
8 1024
 
1.3%
Other values (15) 915
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 63871
80.0%
Other Punctuation 15967
 
20.0%
Uppercase Letter 29
 
< 0.1%
Space Separator 5
 
< 0.1%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 5
17.2%
N 4
13.8%
C 4
13.8%
O 4
13.8%
V 3
10.3%
I 2
 
6.9%
T 2
 
6.9%
D 1
 
3.4%
S 1
 
3.4%
B 1
 
3.4%
Other values (2) 2
 
6.9%
Decimal Number
ValueCountFrequency (%)
2 22497
35.2%
0 19188
30.0%
3 5932
 
9.3%
1 4371
 
6.8%
5 3598
 
5.6%
4 3478
 
5.4%
6 1721
 
2.7%
7 1184
 
1.9%
8 1024
 
1.6%
9 878
 
1.4%
Other Punctuation
ValueCountFrequency (%)
/ 15967
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 79846
> 99.9%
Latin 29
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
2 22497
28.2%
0 19188
24.0%
/ 15967
20.0%
3 5932
 
7.4%
1 4371
 
5.5%
5 3598
 
4.5%
4 3478
 
4.4%
6 1721
 
2.2%
7 1184
 
1.5%
8 1024
 
1.3%
Other values (3) 886
 
1.1%
Latin
ValueCountFrequency (%)
A 5
17.2%
N 4
13.8%
C 4
13.8%
O 4
13.8%
V 3
10.3%
I 2
 
6.9%
T 2
 
6.9%
D 1
 
3.4%
S 1
 
3.4%
B 1
 
3.4%
Other values (2) 2
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 79875
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 22497
28.2%
0 19188
24.0%
/ 15967
20.0%
3 5932
 
7.4%
1 4371
 
5.5%
5 3598
 
4.5%
4 3478
 
4.4%
6 1721
 
2.2%
7 1184
 
1.5%
8 1024
 
1.3%
Other values (15) 915
 
1.1%

MAE_VAC
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct7
Distinct (%)< 0.1%
Missing220304
Missing (%)93.5%
Memory size9.3 MiB
9
9897 
2
4295 
1
1182 
06/02/2023
 
1
6
 
1
Other values (2)
 
2

Length

Max length10
Median length1
Mean length1.0011705
Min length1

Characters and Unicode

Total characters15396
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st row9
2nd row9
3rd row2
4th row9
5th row9

Common Values

ValueCountFrequency (%)
9 9897
 
4.2%
2 4295
 
1.8%
1 1182
 
0.5%
06/02/2023 1
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
17/06/2023 1
 
< 0.1%
(Missing) 220304
93.5%

Length

2023-09-22T21:41:34.706375image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:34.901211image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
9 9897
64.4%
2 4295
27.9%
1 1182
 
7.7%
06/02/2023 1
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
17/06/2023 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
9 9897
64.3%
2 4300
27.9%
1 1183
 
7.7%
0 5
 
< 0.1%
/ 4
 
< 0.1%
6 3
 
< 0.1%
3 2
 
< 0.1%
5 1
 
< 0.1%
7 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15392
> 99.9%
Other Punctuation 4
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 9897
64.3%
2 4300
27.9%
1 1183
 
7.7%
0 5
 
< 0.1%
6 3
 
< 0.1%
3 2
 
< 0.1%
5 1
 
< 0.1%
7 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
/ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15396
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
9 9897
64.3%
2 4300
27.9%
1 1183
 
7.7%
0 5
 
< 0.1%
/ 4
 
< 0.1%
6 3
 
< 0.1%
3 2
 
< 0.1%
5 1
 
< 0.1%
7 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15396
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 9897
64.3%
2 4300
27.9%
1 1183
 
7.7%
0 5
 
< 0.1%
/ 4
 
< 0.1%
6 3
 
< 0.1%
3 2
 
< 0.1%
5 1
 
< 0.1%
7 1
 
< 0.1%

DT_VAC_MAE
Text

MISSING 

Distinct284
Distinct (%)54.6%
Missing235162
Missing (%)99.8%
Memory size7.2 MiB
2023-09-22T21:41:35.230182image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length43
Median length10
Mean length10.011538
Min length1

Characters and Unicode

Total characters5206
Distinct characters30
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique152 ?
Unique (%)29.2%

Sample

1st row30/11/2022
2nd row06/02/2023
3rd row20/09/2021
4th row1
5th row06/06/2023
ValueCountFrequency (%)
15/05/2023 7
 
1.3%
10/05/2023 7
 
1.3%
14/04/2023 6
 
1.1%
19/04/2023 6
 
1.1%
01/04/2022 5
 
1.0%
25/04/2023 5
 
1.0%
31/05/2023 5
 
1.0%
30/03/2023 5
 
1.0%
03/05/2023 5
 
1.0%
17/05/2023 5
 
1.0%
Other values (279) 470
89.4%
2023-09-22T21:41:35.768196image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1531
29.4%
0 1230
23.6%
/ 1032
19.8%
1 421
 
8.1%
3 315
 
6.1%
5 161
 
3.1%
4 138
 
2.7%
6 88
 
1.7%
8 86
 
1.7%
7 84
 
1.6%
Other values (20) 120
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4136
79.4%
Other Punctuation 1032
 
19.8%
Uppercase Letter 29
 
0.6%
Space Separator 6
 
0.1%
Dash Punctuation 3
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
I 4
13.8%
E 3
10.3%
T 2
 
6.9%
A 2
 
6.9%
N 2
 
6.9%
R 2
 
6.9%
V 2
 
6.9%
O 2
 
6.9%
C 2
 
6.9%
Z 1
 
3.4%
Other values (7) 7
24.1%
Decimal Number
ValueCountFrequency (%)
2 1531
37.0%
0 1230
29.7%
1 421
 
10.2%
3 315
 
7.6%
5 161
 
3.9%
4 138
 
3.3%
6 88
 
2.1%
8 86
 
2.1%
7 84
 
2.0%
9 82
 
2.0%
Other Punctuation
ValueCountFrequency (%)
/ 1032
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5177
99.4%
Latin 29
 
0.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
I 4
13.8%
E 3
10.3%
T 2
 
6.9%
A 2
 
6.9%
N 2
 
6.9%
R 2
 
6.9%
V 2
 
6.9%
O 2
 
6.9%
C 2
 
6.9%
Z 1
 
3.4%
Other values (7) 7
24.1%
Common
ValueCountFrequency (%)
2 1531
29.6%
0 1230
23.8%
/ 1032
19.9%
1 421
 
8.1%
3 315
 
6.1%
5 161
 
3.1%
4 138
 
2.7%
6 88
 
1.7%
8 86
 
1.7%
7 84
 
1.6%
Other values (3) 91
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5206
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1531
29.4%
0 1230
23.6%
/ 1032
19.8%
1 421
 
8.1%
3 315
 
6.1%
5 161
 
3.1%
4 138
 
2.7%
6 88
 
1.7%
8 86
 
1.7%
7 84
 
1.6%
Other values (20) 120
 
2.3%

M_AMAMENTA
Categorical

HIGH CORRELATION  MISSING 

Distinct6
Distinct (%)< 0.1%
Missing221321
Missing (%)93.9%
Memory size9.2 MiB
9
6129 
1
5692 
2
2537 
4
 
1
86 - COVID-19 SINOVAC/BUTANTAN - CORONAVAC
 
1

Length

Max length42
Median length1
Mean length1.0034817
Min length1

Characters and Unicode

Total characters14411
Distinct characters24
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row9
2nd row2
3rd row2
4th row9
5th row9

Common Values

ValueCountFrequency (%)
9 6129
 
2.6%
1 5692
 
2.4%
2 2537
 
1.1%
4 1
 
< 0.1%
86 - COVID-19 SINOVAC/BUTANTAN - CORONAVAC 1
 
< 0.1%
07/03/2023 1
 
< 0.1%
(Missing) 221321
93.9%

Length

2023-09-22T21:41:35.979583image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:36.173540image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
9 6129
42.7%
1 5692
39.6%
2 2537
17.7%
2
 
< 0.1%
4 1
 
< 0.1%
86 1
 
< 0.1%
covid-19 1
 
< 0.1%
sinovac/butantan 1
 
< 0.1%
coronavac 1
 
< 0.1%
07/03/2023 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
9 6130
42.5%
1 5693
39.5%
2 2539
17.6%
5
 
< 0.1%
A 5
 
< 0.1%
N 4
 
< 0.1%
C 4
 
< 0.1%
O 4
 
< 0.1%
0 3
 
< 0.1%
/ 3
 
< 0.1%
Other values (14) 21
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14371
99.7%
Uppercase Letter 29
 
0.2%
Space Separator 5
 
< 0.1%
Other Punctuation 3
 
< 0.1%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 5
17.2%
N 4
13.8%
C 4
13.8%
O 4
13.8%
V 3
10.3%
T 2
 
6.9%
I 2
 
6.9%
S 1
 
3.4%
B 1
 
3.4%
U 1
 
3.4%
Other values (2) 2
 
6.9%
Decimal Number
ValueCountFrequency (%)
9 6130
42.7%
1 5693
39.6%
2 2539
17.7%
0 3
 
< 0.1%
3 2
 
< 0.1%
6 1
 
< 0.1%
8 1
 
< 0.1%
4 1
 
< 0.1%
7 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
5
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14382
99.8%
Latin 29
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
9 6130
42.6%
1 5693
39.6%
2 2539
17.7%
5
 
< 0.1%
0 3
 
< 0.1%
/ 3
 
< 0.1%
- 3
 
< 0.1%
3 2
 
< 0.1%
6 1
 
< 0.1%
8 1
 
< 0.1%
Other values (2) 2
 
< 0.1%
Latin
ValueCountFrequency (%)
A 5
17.2%
N 4
13.8%
C 4
13.8%
O 4
13.8%
V 3
10.3%
T 2
 
6.9%
I 2
 
6.9%
S 1
 
3.4%
B 1
 
3.4%
U 1
 
3.4%
Other values (2) 2
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14411
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 6130
42.5%
1 5693
39.5%
2 2539
17.6%
5
 
< 0.1%
A 5
 
< 0.1%
N 4
 
< 0.1%
C 4
 
< 0.1%
O 4
 
< 0.1%
0 3
 
< 0.1%
/ 3
 
< 0.1%
Other values (14) 21
 
0.1%

DT_DOSEUNI
Text

MISSING 

Distinct142
Distinct (%)62.0%
Missing235453
Missing (%)99.9%
Memory size7.2 MiB
2023-09-22T21:41:36.479939image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.8427948
Min length1

Characters and Unicode

Total characters2254
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique93 ?
Unique (%)40.6%

Sample

1st row15/02/2020
2nd row02/06/2022
3rd row18/07/2022
4th row4
5th row21/06/2022
ValueCountFrequency (%)
15/04/2023 9
 
3.9%
25/05/2023 6
 
2.6%
11/04/2023 5
 
2.2%
12/04/2023 5
 
2.2%
31/05/2023 5
 
2.2%
06/05/2023 5
 
2.2%
20/06/2022 4
 
1.7%
19/04/2023 4
 
1.7%
20/04/2023 4
 
1.7%
30/04/2022 4
 
1.7%
Other values (132) 178
77.7%
2023-09-22T21:41:37.091799image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 624
27.7%
0 533
23.6%
/ 448
19.9%
3 165
 
7.3%
1 142
 
6.3%
5 101
 
4.5%
4 74
 
3.3%
6 47
 
2.1%
7 47
 
2.1%
8 44
 
2.0%
Other values (3) 29
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1804
80.0%
Other Punctuation 448
 
19.9%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 624
34.6%
0 533
29.5%
3 165
 
9.1%
1 142
 
7.9%
5 101
 
5.6%
4 74
 
4.1%
6 47
 
2.6%
7 47
 
2.6%
8 44
 
2.4%
9 27
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
S 1
50.0%
P 1
50.0%
Other Punctuation
ValueCountFrequency (%)
/ 448
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2252
99.9%
Latin 2
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
2 624
27.7%
0 533
23.7%
/ 448
19.9%
3 165
 
7.3%
1 142
 
6.3%
5 101
 
4.5%
4 74
 
3.3%
6 47
 
2.1%
7 47
 
2.1%
8 44
 
2.0%
Latin
ValueCountFrequency (%)
S 1
50.0%
P 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2254
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 624
27.7%
0 533
23.6%
/ 448
19.9%
3 165
 
7.3%
1 142
 
6.3%
5 101
 
4.5%
4 74
 
3.3%
6 47
 
2.1%
7 47
 
2.1%
8 44
 
2.0%
Other values (3) 29
 
1.3%

DT_1_DOSE
Text

MISSING 

Distinct156
Distinct (%)68.7%
Missing235455
Missing (%)99.9%
Memory size7.2 MiB
2023-09-22T21:41:37.431702image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length16
Median length10
Mean length9.9471366
Min length1

Characters and Unicode

Total characters2258
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique110 ?
Unique (%)48.5%

Sample

1st row22/05/2023
2nd row20/05/2021
3rd row10/01/2023
4th row09/08/2023
5th row12/05/2021
ValueCountFrequency (%)
26/05/2023 4
 
1.7%
14/04/2023 4
 
1.7%
03/05/2023 4
 
1.7%
22/05/2023 4
 
1.7%
24/04/2023 4
 
1.7%
04/04/2023 4
 
1.7%
15/04/2023 4
 
1.7%
25/04/2023 4
 
1.7%
11/01/2023 3
 
1.3%
01/06/2023 3
 
1.3%
Other values (148) 191
83.4%
2023-09-22T21:41:38.155803image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 627
27.8%
0 523
23.2%
/ 448
19.8%
1 171
 
7.6%
3 159
 
7.0%
5 89
 
3.9%
4 74
 
3.3%
6 43
 
1.9%
7 38
 
1.7%
9 37
 
1.6%
Other values (13) 49
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1794
79.5%
Other Punctuation 448
 
19.8%
Uppercase Letter 14
 
0.6%
Space Separator 2
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
V 2
14.3%
U 2
14.3%
T 2
14.3%
O 1
7.1%
C 1
7.1%
G 1
7.1%
B 1
7.1%
I 1
7.1%
X 1
7.1%
E 1
7.1%
Decimal Number
ValueCountFrequency (%)
2 627
34.9%
0 523
29.2%
1 171
 
9.5%
3 159
 
8.9%
5 89
 
5.0%
4 74
 
4.1%
6 43
 
2.4%
7 38
 
2.1%
9 37
 
2.1%
8 33
 
1.8%
Other Punctuation
ValueCountFrequency (%)
/ 448
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2244
99.4%
Latin 14
 
0.6%

Most frequent character per script

Common
ValueCountFrequency (%)
2 627
27.9%
0 523
23.3%
/ 448
20.0%
1 171
 
7.6%
3 159
 
7.1%
5 89
 
4.0%
4 74
 
3.3%
6 43
 
1.9%
7 38
 
1.7%
9 37
 
1.6%
Other values (2) 35
 
1.6%
Latin
ValueCountFrequency (%)
V 2
14.3%
U 2
14.3%
T 2
14.3%
O 1
7.1%
C 1
7.1%
G 1
7.1%
B 1
7.1%
I 1
7.1%
X 1
7.1%
E 1
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2258
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 627
27.8%
0 523
23.2%
/ 448
19.8%
1 171
 
7.6%
3 159
 
7.0%
5 89
 
3.9%
4 74
 
3.3%
6 43
 
1.9%
7 38
 
1.7%
9 37
 
1.6%
Other values (13) 49
 
2.2%

DT_2_DOSE
Text

MISSING 

Distinct128
Distinct (%)76.6%
Missing235515
Missing (%)99.9%
Memory size7.2 MiB
2023-09-22T21:41:38.563901image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.8862275
Min length1

Characters and Unicode

Total characters1651
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique95 ?
Unique (%)56.9%

Sample

1st row05/08/2022
2nd row17/06/2021
3rd row10/07/2021
4th row29/06/2022
5th row01/09/2023
ValueCountFrequency (%)
26/08/2022 4
 
2.4%
15/05/2023 4
 
2.4%
06/07/2023 3
 
1.8%
19/12/2022 3
 
1.8%
18/01/2023 2
 
1.2%
14/07/2022 2
 
1.2%
12/06/2023 2
 
1.2%
20/06/2022 2
 
1.2%
27/06/2023 2
 
1.2%
14/08/2023 2
 
1.2%
Other values (118) 141
84.4%
2023-09-22T21:41:39.367792image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 458
27.7%
0 376
22.8%
/ 328
19.9%
1 144
 
8.7%
3 99
 
6.0%
6 57
 
3.5%
7 54
 
3.3%
5 43
 
2.6%
9 37
 
2.2%
4 32
 
1.9%
Other values (3) 23
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1321
80.0%
Other Punctuation 328
 
19.9%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 458
34.7%
0 376
28.5%
1 144
 
10.9%
3 99
 
7.5%
6 57
 
4.3%
7 54
 
4.1%
5 43
 
3.3%
9 37
 
2.8%
4 32
 
2.4%
8 21
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
G 1
50.0%
F 1
50.0%
Other Punctuation
ValueCountFrequency (%)
/ 328
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1649
99.9%
Latin 2
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
2 458
27.8%
0 376
22.8%
/ 328
19.9%
1 144
 
8.7%
3 99
 
6.0%
6 57
 
3.5%
7 54
 
3.3%
5 43
 
2.6%
9 37
 
2.2%
4 32
 
1.9%
Latin
ValueCountFrequency (%)
G 1
50.0%
F 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1651
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 458
27.7%
0 376
22.8%
/ 328
19.9%
1 144
 
8.7%
3 99
 
6.0%
6 57
 
3.5%
7 54
 
3.3%
5 43
 
2.6%
9 37
 
2.2%
4 32
 
1.9%
Other values (3) 23
 
1.4%

ANTIVIRAL
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct5
Distinct (%)< 0.1%
Missing44488
Missing (%)18.9%
Memory size12.3 MiB
2
152284 
9
22819 
1
16089 
AVARE
 
1
26/05/2021
 
1

Length

Max length10
Median length1
Mean length1.000068
Min length1

Characters and Unicode

Total characters191207
Distinct characters11
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 152284
64.6%
9 22819
 
9.7%
1 16089
 
6.8%
AVARE 1
 
< 0.1%
26/05/2021 1
 
< 0.1%
(Missing) 44488
 
18.9%

Length

2023-09-22T21:41:39.857677image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:40.280874image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
2 152284
79.6%
9 22819
 
11.9%
1 16089
 
8.4%
avare 1
 
< 0.1%
26/05/2021 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
2 152287
79.6%
9 22819
 
11.9%
1 16090
 
8.4%
A 2
 
< 0.1%
/ 2
 
< 0.1%
0 2
 
< 0.1%
V 1
 
< 0.1%
R 1
 
< 0.1%
E 1
 
< 0.1%
6 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 191200
> 99.9%
Uppercase Letter 5
 
< 0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 152287
79.6%
9 22819
 
11.9%
1 16090
 
8.4%
0 2
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
A 2
40.0%
V 1
20.0%
R 1
20.0%
E 1
20.0%
Other Punctuation
ValueCountFrequency (%)
/ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 191202
> 99.9%
Latin 5
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
2 152287
79.6%
9 22819
 
11.9%
1 16090
 
8.4%
/ 2
 
< 0.1%
0 2
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
Latin
ValueCountFrequency (%)
A 2
40.0%
V 1
20.0%
R 1
20.0%
E 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 191207
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 152287
79.6%
9 22819
 
11.9%
1 16090
 
8.4%
A 2
 
< 0.1%
/ 2
 
< 0.1%
0 2
 
< 0.1%
V 1
 
< 0.1%
R 1
 
< 0.1%
E 1
 
< 0.1%
6 1
 
< 0.1%

TP_ANTIVIR
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct6
Distinct (%)< 0.1%
Missing220347
Missing (%)93.5%
Memory size9.3 MiB
1
14554 
3
 
720
2
 
58
28/02/2023
 
1
350450
 
1

Length

Max length10
Median length1
Mean length1.0014998
Min length1

Characters and Unicode

Total characters15358
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row1
3rd row3
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 14554
 
6.2%
3 720
 
0.3%
2 58
 
< 0.1%
28/02/2023 1
 
< 0.1%
350450 1
 
< 0.1%
30/03/2022 1
 
< 0.1%
(Missing) 220347
93.5%

Length

2023-09-22T21:41:40.685671image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:41.317629image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1 14554
94.9%
3 720
 
4.7%
2 58
 
0.4%
28/02/2023 1
 
< 0.1%
350450 1
 
< 0.1%
30/03/2022 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
1 14554
94.8%
3 724
 
4.7%
2 65
 
0.4%
0 7
 
< 0.1%
/ 4
 
< 0.1%
5 2
 
< 0.1%
8 1
 
< 0.1%
4 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15354
> 99.9%
Other Punctuation 4
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14554
94.8%
3 724
 
4.7%
2 65
 
0.4%
0 7
 
< 0.1%
5 2
 
< 0.1%
8 1
 
< 0.1%
4 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
/ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15358
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14554
94.8%
3 724
 
4.7%
2 65
 
0.4%
0 7
 
< 0.1%
/ 4
 
< 0.1%
5 2
 
< 0.1%
8 1
 
< 0.1%
4 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15358
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14554
94.8%
3 724
 
4.7%
2 65
 
0.4%
0 7
 
< 0.1%
/ 4
 
< 0.1%
5 2
 
< 0.1%
8 1
 
< 0.1%
4 1
 
< 0.1%

OUT_ANTIV
Text

MISSING 

Distinct150
Distinct (%)23.9%
Missing235055
Missing (%)99.7%
Memory size7.2 MiB
2023-09-22T21:41:41.684031image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length43
Median length30
Mean length10.586922
Min length1

Characters and Unicode

Total characters6638
Distinct characters63
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique112 ?
Unique (%)17.9%

Sample

1st rowCEFTRIAXONA
2nd rowCEFTRIAXONA
3rd rowCEFTRIOXONA
4th rowCEFTRIAXONA
5th rowCEFTRIAXONA
ValueCountFrequency (%)
ceftriaxona 288
42.7%
tamiflu 91
 
13.5%
tamiflur 37
 
5.5%
azitromicina 26
 
3.9%
aciclovir 15
 
2.2%
dipirona 10
 
1.5%
remdesivir 9
 
1.3%
ceftrioxona 8
 
1.2%
paracetamol 8
 
1.2%
xarope 6
 
0.9%
Other values (134) 177
26.2%
2023-09-22T21:41:42.266346image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 750
 
11.3%
I 510
 
7.7%
T 400
 
6.0%
R 387
 
5.8%
O 385
 
5.8%
C 374
 
5.6%
E 371
 
5.6%
N 363
 
5.5%
F 352
 
5.3%
X 308
 
4.6%
Other values (53) 2438
36.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 4564
68.8%
Lowercase Letter 1961
29.5%
Space Separator 49
 
0.7%
Decimal Number 30
 
0.5%
Other Punctuation 26
 
0.4%
Math Symbol 5
 
0.1%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 750
16.4%
I 510
11.2%
T 400
8.8%
R 387
8.5%
O 385
8.4%
C 374
8.2%
E 371
8.1%
N 363
8.0%
F 352
7.7%
X 308
6.7%
Other values (15) 364
8.0%
Lowercase Letter
ValueCountFrequency (%)
i 298
15.2%
a 236
12.0%
r 158
8.1%
m 152
 
7.8%
l 143
 
7.3%
t 141
 
7.2%
f 124
 
6.3%
e 113
 
5.8%
u 109
 
5.6%
o 104
 
5.3%
Other values (14) 383
19.5%
Decimal Number
ValueCountFrequency (%)
5 6
20.0%
0 6
20.0%
1 5
16.7%
2 4
13.3%
3 3
10.0%
7 3
10.0%
9 1
 
3.3%
4 1
 
3.3%
6 1
 
3.3%
Other Punctuation
ValueCountFrequency (%)
, 18
69.2%
/ 8
30.8%
Space Separator
ValueCountFrequency (%)
49
100.0%
Math Symbol
ValueCountFrequency (%)
+ 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6525
98.3%
Common 113
 
1.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 750
 
11.5%
I 510
 
7.8%
T 400
 
6.1%
R 387
 
5.9%
O 385
 
5.9%
C 374
 
5.7%
E 371
 
5.7%
N 363
 
5.6%
F 352
 
5.4%
X 308
 
4.7%
Other values (39) 2325
35.6%
Common
ValueCountFrequency (%)
49
43.4%
, 18
 
15.9%
/ 8
 
7.1%
5 6
 
5.3%
0 6
 
5.3%
1 5
 
4.4%
+ 5
 
4.4%
2 4
 
3.5%
- 3
 
2.7%
3 3
 
2.7%
Other values (4) 6
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6632
99.9%
None 6
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 750
 
11.3%
I 510
 
7.7%
T 400
 
6.0%
R 387
 
5.8%
O 385
 
5.8%
C 374
 
5.6%
E 371
 
5.6%
N 363
 
5.5%
F 352
 
5.3%
X 308
 
4.6%
Other values (50) 2432
36.7%
None
ValueCountFrequency (%)
à 3
50.0%
Ó 2
33.3%
Í 1
 
16.7%

DT_ANTIVIR
Text

MISSING 

Distinct271
Distinct (%)1.9%
Missing221687
Missing (%)94.1%
Memory size7.7 MiB
2023-09-22T21:41:42.660772image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length46
Median length10
Mean length10.000429
Min length1

Characters and Unicode

Total characters139956
Distinct characters30
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)0.1%

Sample

1st row18/02/2023
2nd row04/02/2023
3rd row02/02/2023
4th row15/04/2023
5th row30/03/2023
ValueCountFrequency (%)
22/05/2023 136
 
1.0%
30/05/2023 133
 
0.9%
29/05/2023 131
 
0.9%
25/05/2023 126
 
0.9%
24/05/2023 121
 
0.9%
23/05/2023 120
 
0.9%
09/05/2023 119
 
0.9%
17/05/2023 118
 
0.8%
24/04/2023 117
 
0.8%
18/05/2023 116
 
0.8%
Other values (265) 12763
91.2%
2023-09-22T21:41:43.174161image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 34891
24.9%
0 33378
23.8%
/ 27981
20.0%
3 17841
12.7%
1 6727
 
4.8%
5 4524
 
3.2%
4 3847
 
2.7%
6 3717
 
2.7%
7 2807
 
2.0%
8 2482
 
1.8%
Other values (20) 1761
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 111930
80.0%
Other Punctuation 27981
 
20.0%
Uppercase Letter 37
 
< 0.1%
Space Separator 5
 
< 0.1%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 5
13.5%
I 4
10.8%
S 3
 
8.1%
O 3
 
8.1%
E 3
 
8.1%
A 3
 
8.1%
V 2
 
5.4%
D 2
 
5.4%
F 2
 
5.4%
R 2
 
5.4%
Other values (7) 8
21.6%
Decimal Number
ValueCountFrequency (%)
2 34891
31.2%
0 33378
29.8%
3 17841
15.9%
1 6727
 
6.0%
5 4524
 
4.0%
4 3847
 
3.4%
6 3717
 
3.3%
7 2807
 
2.5%
8 2482
 
2.2%
9 1716
 
1.5%
Other Punctuation
ValueCountFrequency (%)
/ 27981
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 139919
> 99.9%
Latin 37
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
C 5
13.5%
I 4
10.8%
S 3
 
8.1%
O 3
 
8.1%
E 3
 
8.1%
A 3
 
8.1%
V 2
 
5.4%
D 2
 
5.4%
F 2
 
5.4%
R 2
 
5.4%
Other values (7) 8
21.6%
Common
ValueCountFrequency (%)
2 34891
24.9%
0 33378
23.9%
/ 27981
20.0%
3 17841
12.8%
1 6727
 
4.8%
5 4524
 
3.2%
4 3847
 
2.7%
6 3717
 
2.7%
7 2807
 
2.0%
8 2482
 
1.8%
Other values (3) 1724
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 139956
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 34891
24.9%
0 33378
23.8%
/ 27981
20.0%
3 17841
12.7%
1 6727
 
4.8%
5 4524
 
3.2%
4 3847
 
2.7%
6 3717
 
2.7%
7 2807
 
2.0%
8 2482
 
1.8%
Other values (20) 1761
 
1.3%

HOSPITAL
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct7
Distinct (%)< 0.1%
Missing6769
Missing (%)2.9%
Memory size12.9 MiB
1
224104 
2
 
4399
9
 
406
CHAPECO
 
1
23/08/2023
 
1
Other values (2)
 
2

Length

Max length35
Median length1
Mean length1.0002534
Min length1

Characters and Unicode

Total characters228971
Distinct characters24
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 224104
95.1%
2 4399
 
1.9%
9 406
 
0.2%
CHAPECO 1
 
< 0.1%
23/08/2023 1
 
< 0.1%
07/03/2023 1
 
< 0.1%
88 - COVID-19 JANSSEN - AD26.COV2.S 1
 
< 0.1%
(Missing) 6769
 
2.9%

Length

2023-09-22T21:41:43.382606image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:43.579503image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1 224104
97.9%
2 4399
 
1.9%
9 406
 
0.2%
2
 
< 0.1%
chapeco 1
 
< 0.1%
23/08/2023 1
 
< 0.1%
07/03/2023 1
 
< 0.1%
88 1
 
< 0.1%
covid-19 1
 
< 0.1%
janssen 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
1 224105
97.9%
2 4406
 
1.9%
9 407
 
0.2%
5
 
< 0.1%
0 5
 
< 0.1%
/ 4
 
< 0.1%
C 4
 
< 0.1%
3 4
 
< 0.1%
S 3
 
< 0.1%
- 3
 
< 0.1%
Other values (14) 25
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 228932
> 99.9%
Uppercase Letter 25
 
< 0.1%
Other Punctuation 6
 
< 0.1%
Space Separator 5
 
< 0.1%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 4
16.0%
S 3
12.0%
O 3
12.0%
A 3
12.0%
E 2
8.0%
V 2
8.0%
D 2
8.0%
N 2
8.0%
P 1
 
4.0%
I 1
 
4.0%
Other values (2) 2
8.0%
Decimal Number
ValueCountFrequency (%)
1 224105
97.9%
2 4406
 
1.9%
9 407
 
0.2%
0 5
 
< 0.1%
3 4
 
< 0.1%
8 3
 
< 0.1%
7 1
 
< 0.1%
6 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
/ 4
66.7%
. 2
33.3%
Space Separator
ValueCountFrequency (%)
5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 228946
> 99.9%
Latin 25
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 224105
97.9%
2 4406
 
1.9%
9 407
 
0.2%
5
 
< 0.1%
0 5
 
< 0.1%
/ 4
 
< 0.1%
3 4
 
< 0.1%
- 3
 
< 0.1%
8 3
 
< 0.1%
. 2
 
< 0.1%
Other values (2) 2
 
< 0.1%
Latin
ValueCountFrequency (%)
C 4
16.0%
S 3
12.0%
O 3
12.0%
A 3
12.0%
E 2
8.0%
V 2
8.0%
D 2
8.0%
N 2
8.0%
P 1
 
4.0%
I 1
 
4.0%
Other values (2) 2
8.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 228971
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 224105
97.9%
2 4406
 
1.9%
9 407
 
0.2%
5
 
< 0.1%
0 5
 
< 0.1%
/ 4
 
< 0.1%
C 4
 
< 0.1%
3 4
 
< 0.1%
S 3
 
< 0.1%
- 3
 
< 0.1%
Other values (14) 25
 
< 0.1%

DT_INTERNA
Text

MISSING 

Distinct355
Distinct (%)0.2%
Missing14757
Missing (%)6.3%
Memory size14.6 MiB
2023-09-22T21:41:43.905337image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length27
Median length10
Mean length9.9999321
Min length1

Characters and Unicode

Total characters2209235
Distinct characters26
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)< 0.1%

Sample

1st row03/01/2023
2nd row08/01/2023
3rd row22/01/2023
4th row05/02/2023
5th row25/01/2023
ValueCountFrequency (%)
23/05/2023 1407
 
0.6%
22/05/2023 1401
 
0.6%
24/04/2023 1326
 
0.6%
28/03/2023 1319
 
0.6%
15/05/2023 1311
 
0.6%
02/05/2023 1298
 
0.6%
25/05/2023 1298
 
0.6%
18/04/2023 1285
 
0.6%
29/05/2023 1283
 
0.6%
08/05/2023 1282
 
0.6%
Other values (347) 207717
94.0%
2023-09-22T21:41:44.425822image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 557521
25.2%
0 528712
23.9%
/ 441842
20.0%
3 285401
12.9%
1 119047
 
5.4%
5 57879
 
2.6%
4 54357
 
2.5%
6 51427
 
2.3%
7 45059
 
2.0%
8 40856
 
1.8%
Other values (16) 27134
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1767374
80.0%
Other Punctuation 441843
 
20.0%
Uppercase Letter 15
 
< 0.1%
Space Separator 2
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R 2
13.3%
I 2
13.3%
O 2
13.3%
Z 1
6.7%
E 1
6.7%
G 1
6.7%
C 1
6.7%
M 1
6.7%
N 1
6.7%
A 1
6.7%
Other values (2) 2
13.3%
Decimal Number
ValueCountFrequency (%)
2 557521
31.5%
0 528712
29.9%
3 285401
16.1%
1 119047
 
6.7%
5 57879
 
3.3%
4 54357
 
3.1%
6 51427
 
2.9%
7 45059
 
2.5%
8 40856
 
2.3%
9 27115
 
1.5%
Other Punctuation
ValueCountFrequency (%)
/ 441842
> 99.9%
" 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2209220
> 99.9%
Latin 15
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
2 557521
25.2%
0 528712
23.9%
/ 441842
20.0%
3 285401
12.9%
1 119047
 
5.4%
5 57879
 
2.6%
4 54357
 
2.5%
6 51427
 
2.3%
7 45059
 
2.0%
8 40856
 
1.8%
Other values (4) 27119
 
1.2%
Latin
ValueCountFrequency (%)
R 2
13.3%
I 2
13.3%
O 2
13.3%
Z 1
6.7%
E 1
6.7%
G 1
6.7%
C 1
6.7%
M 1
6.7%
N 1
6.7%
A 1
6.7%
Other values (2) 2
13.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2209235
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 557521
25.2%
0 528712
23.9%
/ 441842
20.0%
3 285401
12.9%
1 119047
 
5.4%
5 57879
 
2.6%
4 54357
 
2.5%
6 51427
 
2.3%
7 45059
 
2.0%
8 40856
 
1.8%
Other values (16) 27134
 
1.2%

SG_UF_INTE
Categorical

HIGH CORRELATION  MISSING 

Distinct31
Distinct (%)< 0.1%
Missing20135
Missing (%)8.5%
Memory size12.9 MiB
SP
61560 
PR
23136 
MG
19055 
RJ
14330 
RS
12005 
Other values (26)
85461 

Length

Max length8
Median length2
Mean length2.0000603
Min length1

Characters and Unicode

Total characters431107
Distinct characters22
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st rowMG
2nd rowRJ
3rd rowSP
4th rowSP
5th rowSP

Common Values

ValueCountFrequency (%)
SP 61560
26.1%
PR 23136
 
9.8%
MG 19055
 
8.1%
RJ 14330
 
6.1%
RS 12005
 
5.1%
DF 9538
 
4.0%
SC 9379
 
4.0%
CE 9283
 
3.9%
BA 8221
 
3.5%
PE 6595
 
2.8%
Other values (21) 42445
18.0%
(Missing) 20135
 
8.5%

Length

2023-09-22T21:41:44.639038image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
sp 61560
28.6%
pr 23136
 
10.7%
mg 19055
 
8.8%
rj 14330
 
6.6%
rs 12005
 
5.6%
df 9538
 
4.4%
sc 9379
 
4.4%
ce 9283
 
4.3%
ba 8221
 
3.8%
pe 6595
 
3.1%
Other values (22) 42446
19.7%

Most occurring characters

ValueCountFrequency (%)
P 101683
23.6%
S 95327
22.1%
R 53722
12.5%
M 32069
 
7.4%
G 24780
 
5.7%
E 21808
 
5.1%
A 21689
 
5.0%
C 20538
 
4.8%
J 14330
 
3.3%
B 11813
 
2.7%
Other values (12) 33348
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 431100
> 99.9%
Decimal Number 6
 
< 0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
P 101683
23.6%
S 95327
22.1%
R 53722
12.5%
M 32069
 
7.4%
G 24780
 
5.7%
E 21808
 
5.1%
A 21689
 
5.0%
C 20538
 
4.8%
J 14330
 
3.3%
B 11813
 
2.7%
Other values (8) 33341
 
7.7%
Decimal Number
ValueCountFrequency (%)
2 3
50.0%
8 2
33.3%
4 1
 
16.7%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 431100
> 99.9%
Common 7
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
P 101683
23.6%
S 95327
22.1%
R 53722
12.5%
M 32069
 
7.4%
G 24780
 
5.7%
E 21808
 
5.1%
A 21689
 
5.0%
C 20538
 
4.8%
J 14330
 
3.3%
B 11813
 
2.7%
Other values (8) 33341
 
7.7%
Common
ValueCountFrequency (%)
2 3
42.9%
8 2
28.6%
1
 
14.3%
4 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 431107
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
P 101683
23.6%
S 95327
22.1%
R 53722
12.5%
M 32069
 
7.4%
G 24780
 
5.7%
E 21808
 
5.1%
A 21689
 
5.0%
C 20538
 
4.8%
J 14330
 
3.3%
B 11813
 
2.7%
Other values (12) 33348
 
7.7%

ID_RG_INTE
Text

MISSING 

Distinct301
Distinct (%)0.2%
Missing47020
Missing (%)20.0%
Memory size14.6 MiB
2023-09-22T21:41:44.950594image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length50
Median length42
Mean length15.894351
Min length3

Characters and Unicode

Total characters2998660
Distinct characters40
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)< 0.1%

Sample

1st rowLEOPOLDINA
2nd rowGVE XV BAURU
3rd rowGVE XIX MARILIA
4th rowGVE XVII CAMPINAS
5th rowNUCLEO REGIONAL DE SAUDE LESTE
ValueCountFrequency (%)
gve 61560
 
11.2%
de 24856
 
4.5%
i 19072
 
3.5%
capital 17182
 
3.1%
regional 16514
 
3.0%
crs 12005
 
2.2%
belo 11326
 
2.1%
horizonte 11326
 
2.1%
metropolitana 11231
 
2.0%
saude 11208
 
2.0%
Other values (387) 353794
64.3%
2023-09-22T21:41:45.508833image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
361914
12.1%
A 298229
 
9.9%
E 269549
 
9.0%
I 233261
 
7.8%
O 229138
 
7.6%
R 212239
 
7.1%
S 160328
 
5.3%
N 128089
 
4.3%
T 113337
 
3.8%
L 112841
 
3.8%
Other values (30) 879735
29.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 2511417
83.8%
Space Separator 361914
 
12.1%
Decimal Number 123738
 
4.1%
Dash Punctuation 1580
 
0.1%
Other Punctuation 11
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 298229
11.9%
E 269549
10.7%
I 233261
 
9.3%
O 229138
 
9.1%
R 212239
 
8.5%
S 160328
 
6.4%
N 128089
 
5.1%
T 113337
 
4.5%
L 112841
 
4.5%
C 112707
 
4.5%
Other values (16) 641699
25.6%
Decimal Number
ValueCountFrequency (%)
0 53859
43.5%
1 33973
27.5%
2 13329
 
10.8%
5 5368
 
4.3%
7 4895
 
4.0%
3 3995
 
3.2%
6 2764
 
2.2%
4 2472
 
2.0%
9 2135
 
1.7%
8 948
 
0.8%
Other Punctuation
ValueCountFrequency (%)
. 10
90.9%
/ 1
 
9.1%
Space Separator
ValueCountFrequency (%)
361914
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1580
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2511417
83.8%
Common 487243
 
16.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 298229
11.9%
E 269549
10.7%
I 233261
 
9.3%
O 229138
 
9.1%
R 212239
 
8.5%
S 160328
 
6.4%
N 128089
 
5.1%
T 113337
 
4.5%
L 112841
 
4.5%
C 112707
 
4.5%
Other values (16) 641699
25.6%
Common
ValueCountFrequency (%)
361914
74.3%
0 53859
 
11.1%
1 33973
 
7.0%
2 13329
 
2.7%
5 5368
 
1.1%
7 4895
 
1.0%
3 3995
 
0.8%
6 2764
 
0.6%
4 2472
 
0.5%
9 2135
 
0.4%
Other values (4) 2539
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2998455
> 99.9%
None 205
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
361914
12.1%
A 298229
 
9.9%
E 269549
 
9.0%
I 233261
 
7.8%
O 229138
 
7.6%
R 212239
 
7.1%
S 160328
 
5.3%
N 128089
 
4.3%
T 113337
 
3.8%
L 112841
 
3.8%
Other values (27) 879530
29.3%
None
ValueCountFrequency (%)
Õ 112
54.6%
É 63
30.7%
Á 30
 
14.6%

CO_RG_INTE
Text

MISSING 

Distinct302
Distinct (%)0.2%
Missing47019
Missing (%)20.0%
Memory size12.4 MiB
2023-09-22T21:41:45.974653image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length24
Median length4
Mean length4.0002014
Min length1

Characters and Unicode

Total characters754690
Distinct characters25
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)< 0.1%

Sample

1st row1453
2nd row1340
3rd row1344
4th row1342
5th row1380
ValueCountFrequency (%)
1331 17182
 
9.1%
1449 11326
 
6.0%
1342 8954
 
4.7%
1356 7510
 
4.0%
1519 5877
 
3.1%
1497 5564
 
2.9%
1354 4703
 
2.5%
1380 4317
 
2.3%
1371 4041
 
2.1%
1975 3958
 
2.1%
Other values (296) 115235
61.1%
2023-09-22T21:41:46.607325image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 230196
30.5%
3 138254
18.3%
4 90844
 
12.0%
5 75334
 
10.0%
9 49212
 
6.5%
6 44004
 
5.8%
7 40891
 
5.4%
8 30212
 
4.0%
2 29371
 
3.9%
0 26340
 
3.5%
Other values (15) 32
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 754658
> 99.9%
Uppercase Letter 22
 
< 0.1%
Other Punctuation 6
 
< 0.1%
Space Separator 4
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 4
18.2%
O 3
13.6%
E 3
13.6%
A 2
9.1%
L 2
9.1%
H 1
 
4.5%
U 1
 
4.5%
I 1
 
4.5%
D 1
 
4.5%
M 1
 
4.5%
Other values (3) 3
13.6%
Decimal Number
ValueCountFrequency (%)
1 230196
30.5%
3 138254
18.3%
4 90844
 
12.0%
5 75334
 
10.0%
9 49212
 
6.5%
6 44004
 
5.8%
7 40891
 
5.4%
8 30212
 
4.0%
2 29371
 
3.9%
0 26340
 
3.5%
Other Punctuation
ValueCountFrequency (%)
/ 6
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 754668
> 99.9%
Latin 22
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 4
18.2%
O 3
13.6%
E 3
13.6%
A 2
9.1%
L 2
9.1%
H 1
 
4.5%
U 1
 
4.5%
I 1
 
4.5%
D 1
 
4.5%
M 1
 
4.5%
Other values (3) 3
13.6%
Common
ValueCountFrequency (%)
1 230196
30.5%
3 138254
18.3%
4 90844
 
12.0%
5 75334
 
10.0%
9 49212
 
6.5%
6 44004
 
5.8%
7 40891
 
5.4%
8 30212
 
4.0%
2 29371
 
3.9%
0 26340
 
3.5%
Other values (2) 10
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 754690
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 230196
30.5%
3 138254
18.3%
4 90844
 
12.0%
5 75334
 
10.0%
9 49212
 
6.5%
6 44004
 
5.8%
7 40891
 
5.4%
8 30212
 
4.0%
2 29371
 
3.9%
0 26340
 
3.5%
Other values (15) 32
 
< 0.1%

ID_MN_INTE
Text

MISSING 

Distinct1455
Distinct (%)0.7%
Missing20134
Missing (%)8.5%
Memory size14.4 MiB
2023-09-22T21:41:46.983878image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length30
Median length26
Mean length10.018891
Min length1

Characters and Unicode

Total characters2159552
Distinct characters32
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique197 ?
Unique (%)0.1%

Sample

1st rowALEM PARAIBA
2nd rowVOLTA REDONDA
3rd rowJAU
4th rowADAMANTINA
5th rowCAMPINAS
ValueCountFrequency (%)
sao 28088
 
8.1%
paulo 17195
 
5.0%
rio 12681
 
3.7%
do 11724
 
3.4%
de 10987
 
3.2%
brasilia 9544
 
2.8%
horizonte 9315
 
2.7%
belo 9235
 
2.7%
janeiro 6777
 
2.0%
campinas 6215
 
1.8%
Other values (1407) 223068
64.7%
2023-09-22T21:41:47.562114image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 364568
16.9%
O 244520
11.3%
R 171014
 
7.9%
I 170037
 
7.9%
E 135650
 
6.3%
129281
 
6.0%
S 124751
 
5.8%
N 102031
 
4.7%
L 102005
 
4.7%
U 81829
 
3.8%
Other values (22) 533866
24.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 2029702
94.0%
Space Separator 129281
 
6.0%
Dash Punctuation 293
 
< 0.1%
Other Punctuation 264
 
< 0.1%
Decimal Number 12
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 364568
18.0%
O 244520
12.0%
R 171014
 
8.4%
I 170037
 
8.4%
E 135650
 
6.7%
S 124751
 
6.1%
N 102031
 
5.0%
L 102005
 
5.0%
U 81829
 
4.0%
T 81509
 
4.0%
Other values (15) 451788
22.3%
Decimal Number
ValueCountFrequency (%)
2 6
50.0%
0 3
25.0%
1 2
 
16.7%
5 1
 
8.3%
Space Separator
ValueCountFrequency (%)
129281
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 293
100.0%
Other Punctuation
ValueCountFrequency (%)
' 264
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2029702
94.0%
Common 129850
 
6.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 364568
18.0%
O 244520
12.0%
R 171014
 
8.4%
I 170037
 
8.4%
E 135650
 
6.7%
S 124751
 
6.1%
N 102031
 
5.0%
L 102005
 
5.0%
U 81829
 
4.0%
T 81509
 
4.0%
Other values (15) 451788
22.3%
Common
ValueCountFrequency (%)
129281
99.6%
- 293
 
0.2%
' 264
 
0.2%
2 6
 
< 0.1%
0 3
 
< 0.1%
1 2
 
< 0.1%
5 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2159552
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 364568
16.9%
O 244520
11.3%
R 171014
 
7.9%
I 170037
 
7.9%
E 135650
 
6.3%
129281
 
6.0%
S 124751
 
5.8%
N 102031
 
4.7%
L 102005
 
4.7%
U 81829
 
3.8%
Other values (22) 533866
24.7%

CO_MU_INTE
Text

MISSING 

Distinct1475
Distinct (%)0.7%
Missing20137
Missing (%)8.5%
Memory size13.6 MiB
2023-09-22T21:41:47.952937image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length6
Mean length6.0000232
Min length1

Characters and Unicode

Total characters1293275
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique207 ?
Unique (%)0.1%

Sample

1st row310150
2nd row330630
3rd row352530
4th row350010
5th row350950
ValueCountFrequency (%)
355030 17182
 
8.0%
530010 9538
 
4.4%
310620 9139
 
4.2%
330455 6777
 
3.1%
350950 6215
 
2.9%
230440 5866
 
2.7%
410690 5672
 
2.6%
292740 4100
 
1.9%
261160 3768
 
1.7%
500270 3518
 
1.6%
Other values (1465) 143770
66.7%
2023-09-22T21:41:48.497640image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 380836
29.4%
3 205895
15.9%
5 159977
12.4%
1 134334
 
10.4%
4 123679
 
9.6%
2 118322
 
9.1%
9 47973
 
3.7%
6 46478
 
3.6%
8 39103
 
3.0%
7 36672
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1293269
> 99.9%
Other Punctuation 6
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 380836
29.4%
3 205895
15.9%
5 159977
12.4%
1 134334
 
10.4%
4 123679
 
9.6%
2 118322
 
9.1%
9 47973
 
3.7%
6 46478
 
3.6%
8 39103
 
3.0%
7 36672
 
2.8%
Other Punctuation
ValueCountFrequency (%)
/ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1293275
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 380836
29.4%
3 205895
15.9%
5 159977
12.4%
1 134334
 
10.4%
4 123679
 
9.6%
2 118322
 
9.1%
9 47973
 
3.7%
6 46478
 
3.6%
8 39103
 
3.0%
7 36672
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1293275
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 380836
29.4%
3 205895
15.9%
5 159977
12.4%
1 134334
 
10.4%
4 123679
 
9.6%
2 118322
 
9.1%
9 47973
 
3.7%
6 46478
 
3.6%
8 39103
 
3.0%
7 36672
 
2.8%

UTI
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct5
Distinct (%)< 0.1%
Missing31152
Missing (%)13.2%
Memory size12.5 MiB
2
141034 
1
60959 
9
 
2535
23/08/2023
 
1
88 - COVID-19 JANSSEN - AD26.COV2.S
 
1

Length

Max length35
Median length1
Mean length1.0002102
Min length1

Characters and Unicode

Total characters204573
Distinct characters21
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row2
2nd row2
3rd row2
4th row1
5th row2

Common Values

ValueCountFrequency (%)
2 141034
59.8%
1 60959
25.9%
9 2535
 
1.1%
23/08/2023 1
 
< 0.1%
88 - COVID-19 JANSSEN - AD26.COV2.S 1
 
< 0.1%
(Missing) 31152
 
13.2%

Length

2023-09-22T21:41:48.708528image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:48.912889image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
2 141034
69.0%
1 60959
29.8%
9 2535
 
1.2%
2
 
< 0.1%
23/08/2023 1
 
< 0.1%
88 1
 
< 0.1%
covid-19 1
 
< 0.1%
janssen 1
 
< 0.1%
ad26.cov2.s 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
2 141039
68.9%
1 60960
29.8%
9 2536
 
1.2%
5
 
< 0.1%
S 3
 
< 0.1%
8 3
 
< 0.1%
- 3
 
< 0.1%
V 2
 
< 0.1%
N 2
 
< 0.1%
A 2
 
< 0.1%
Other values (11) 18
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 204543
> 99.9%
Uppercase Letter 18
 
< 0.1%
Space Separator 5
 
< 0.1%
Other Punctuation 4
 
< 0.1%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 3
16.7%
V 2
11.1%
N 2
11.1%
A 2
11.1%
D 2
11.1%
O 2
11.1%
C 2
11.1%
I 1
 
5.6%
J 1
 
5.6%
E 1
 
5.6%
Decimal Number
ValueCountFrequency (%)
2 141039
69.0%
1 60960
29.8%
9 2536
 
1.2%
8 3
 
< 0.1%
0 2
 
< 0.1%
3 2
 
< 0.1%
6 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
/ 2
50.0%
. 2
50.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 204555
> 99.9%
Latin 18
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
2 141039
68.9%
1 60960
29.8%
9 2536
 
1.2%
5
 
< 0.1%
8 3
 
< 0.1%
- 3
 
< 0.1%
0 2
 
< 0.1%
/ 2
 
< 0.1%
3 2
 
< 0.1%
. 2
 
< 0.1%
Latin
ValueCountFrequency (%)
S 3
16.7%
V 2
11.1%
N 2
11.1%
A 2
11.1%
D 2
11.1%
O 2
11.1%
C 2
11.1%
I 1
 
5.6%
J 1
 
5.6%
E 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 204573
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 141039
68.9%
1 60960
29.8%
9 2536
 
1.2%
5
 
< 0.1%
S 3
 
< 0.1%
8 3
 
< 0.1%
- 3
 
< 0.1%
V 2
 
< 0.1%
N 2
 
< 0.1%
A 2
 
< 0.1%
Other values (11) 18
 
< 0.1%

DT_ENTUTI
Text

MISSING 

Distinct309
Distinct (%)0.5%
Missing176202
Missing (%)74.8%
Memory size9.2 MiB
2023-09-22T21:41:49.226990image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9994956
Min length1

Characters and Unicode

Total characters594770
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)0.1%

Sample

1st row22/01/2023
2nd row25/01/2023
3rd row08/01/2023
4th row18/02/2023
5th row22/01/2023
ValueCountFrequency (%)
11/04/2023 361
 
0.6%
04/04/2023 355
 
0.6%
16/05/2023 354
 
0.6%
25/04/2023 354
 
0.6%
20/03/2023 350
 
0.6%
25/05/2023 337
 
0.6%
24/04/2023 337
 
0.6%
10/04/2023 335
 
0.6%
18/05/2023 334
 
0.6%
15/05/2023 334
 
0.6%
Other values (299) 56029
94.2%
2023-09-22T21:41:49.728479image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 149928
25.2%
0 142422
23.9%
/ 118952
20.0%
3 76741
12.9%
1 32956
 
5.5%
5 15270
 
2.6%
4 14690
 
2.5%
6 13779
 
2.3%
7 11840
 
2.0%
8 10912
 
1.8%
Other values (3) 7280
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 475816
80.0%
Other Punctuation 118952
 
20.0%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 149928
31.5%
0 142422
29.9%
3 76741
16.1%
1 32956
 
6.9%
5 15270
 
3.2%
4 14690
 
3.1%
6 13779
 
2.9%
7 11840
 
2.5%
8 10912
 
2.3%
9 7278
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
H 1
50.0%
A 1
50.0%
Other Punctuation
ValueCountFrequency (%)
/ 118952
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 594768
> 99.9%
Latin 2
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
2 149928
25.2%
0 142422
23.9%
/ 118952
20.0%
3 76741
12.9%
1 32956
 
5.5%
5 15270
 
2.6%
4 14690
 
2.5%
6 13779
 
2.3%
7 11840
 
2.0%
8 10912
 
1.8%
Latin
ValueCountFrequency (%)
H 1
50.0%
A 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 594770
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 149928
25.2%
0 142422
23.9%
/ 118952
20.0%
3 76741
12.9%
1 32956
 
5.5%
5 15270
 
2.6%
4 14690
 
2.5%
6 13779
 
2.3%
7 11840
 
2.0%
8 10912
 
1.8%
Other values (3) 7280
 
1.2%

DT_SAIDUTI
Text

MISSING 

Distinct266
Distinct (%)0.8%
Missing203192
Missing (%)86.2%
Memory size8.3 MiB
2023-09-22T21:41:50.049518image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.998615
Min length1

Characters and Unicode

Total characters324855
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st row30/01/2023
2nd row20/01/2023
3rd row24/02/2023
4th row06/01/2023
5th row11/02/2023
ValueCountFrequency (%)
24/04/2023 223
 
0.7%
10/05/2023 216
 
0.7%
23/05/2023 215
 
0.7%
16/05/2023 205
 
0.6%
06/06/2023 204
 
0.6%
19/04/2023 204
 
0.6%
30/05/2023 203
 
0.6%
29/05/2023 202
 
0.6%
02/05/2023 200
 
0.6%
15/05/2023 199
 
0.6%
Other values (256) 30419
93.6%
2023-09-22T21:41:50.551486image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 82086
25.3%
0 77632
23.9%
/ 64970
20.0%
3 41871
12.9%
1 17231
 
5.3%
5 8620
 
2.7%
4 8009
 
2.5%
6 7876
 
2.4%
7 6838
 
2.1%
8 5922
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 259885
80.0%
Other Punctuation 64970
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 82086
31.6%
0 77632
29.9%
3 41871
16.1%
1 17231
 
6.6%
5 8620
 
3.3%
4 8009
 
3.1%
6 7876
 
3.0%
7 6838
 
2.6%
8 5922
 
2.3%
9 3800
 
1.5%
Other Punctuation
ValueCountFrequency (%)
/ 64970
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 324855
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 82086
25.3%
0 77632
23.9%
/ 64970
20.0%
3 41871
12.9%
1 17231
 
5.3%
5 8620
 
2.7%
4 8009
 
2.5%
6 7876
 
2.4%
7 6838
 
2.1%
8 5922
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 324855
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 82086
25.3%
0 77632
23.9%
/ 64970
20.0%
3 41871
12.9%
1 17231
 
5.3%
5 8620
 
2.7%
4 8009
 
2.5%
6 7876
 
2.4%
7 6838
 
2.1%
8 5922
 
1.8%

SUPORT_VEN
Categorical

HIGH CORRELATION  MISSING 

Distinct5
Distinct (%)< 0.1%
Missing32175
Missing (%)13.7%
Memory size12.5 MiB
2
109488 
3
64612 
1
23793 
9
 
5613
23/05/2023
 
1

Length

Max length10
Median length1
Mean length1.0000442
Min length1

Characters and Unicode

Total characters203516
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row2
2nd row9
3rd row2
4th row3
5th row2

Common Values

ValueCountFrequency (%)
2 109488
46.5%
3 64612
27.4%
1 23793
 
10.1%
9 5613
 
2.4%
23/05/2023 1
 
< 0.1%
(Missing) 32175
 
13.7%

Length

2023-09-22T21:41:50.752173image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:50.940914image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
2 109488
53.8%
3 64612
31.7%
1 23793
 
11.7%
9 5613
 
2.8%
23/05/2023 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
2 109491
53.8%
3 64614
31.7%
1 23793
 
11.7%
9 5613
 
2.8%
/ 2
 
< 0.1%
0 2
 
< 0.1%
5 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 203514
> 99.9%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 109491
53.8%
3 64614
31.7%
1 23793
 
11.7%
9 5613
 
2.8%
0 2
 
< 0.1%
5 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
/ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 203516
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 109491
53.8%
3 64614
31.7%
1 23793
 
11.7%
9 5613
 
2.8%
/ 2
 
< 0.1%
0 2
 
< 0.1%
5 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 203516
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 109491
53.8%
3 64614
31.7%
1 23793
 
11.7%
9 5613
 
2.8%
/ 2
 
< 0.1%
0 2
 
< 0.1%
5 1
 
< 0.1%

RAIOX_RES
Categorical

HIGH CORRELATION  MISSING 

Distinct8
Distinct (%)< 0.1%
Missing84633
Missing (%)35.9%
Memory size11.6 MiB
6
43694 
2
36939 
5
21187 
9
18580 
1
17551 
Other values (3)
13098 

Length

Max length10
Median length1
Mean length1.0000596
Min length1

Characters and Unicode

Total characters151058
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row2
2nd row5
3rd row5
4th row2
5th row5

Common Values

ValueCountFrequency (%)
6 43694
18.5%
2 36939
15.7%
5 21187
 
9.0%
9 18580
 
7.9%
1 17551
 
7.4%
3 8533
 
3.6%
4 4564
 
1.9%
19/03/2023 1
 
< 0.1%
(Missing) 84633
35.9%

Length

2023-09-22T21:41:51.109155image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:51.323622image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
6 43694
28.9%
2 36939
24.5%
5 21187
14.0%
9 18580
12.3%
1 17551
11.6%
3 8533
 
5.6%
4 4564
 
3.0%
19/03/2023 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
6 43694
28.9%
2 36941
24.5%
5 21187
14.0%
9 18581
12.3%
1 17552
11.6%
3 8535
 
5.7%
4 4564
 
3.0%
/ 2
 
< 0.1%
0 2
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 151056
> 99.9%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 43694
28.9%
2 36941
24.5%
5 21187
14.0%
9 18581
12.3%
1 17552
11.6%
3 8535
 
5.7%
4 4564
 
3.0%
0 2
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
/ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 151058
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 43694
28.9%
2 36941
24.5%
5 21187
14.0%
9 18581
12.3%
1 17552
11.6%
3 8535
 
5.7%
4 4564
 
3.0%
/ 2
 
< 0.1%
0 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 151058
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 43694
28.9%
2 36941
24.5%
5 21187
14.0%
9 18581
12.3%
1 17552
11.6%
3 8535
 
5.7%
4 4564
 
3.0%
/ 2
 
< 0.1%
0 2
 
< 0.1%

RAIOX_OUT
Text

MISSING 

Distinct5947
Distinct (%)33.5%
Missing217956
Missing (%)92.5%
Memory size7.9 MiB
2023-09-22T21:41:51.684450image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length45
Median length26
Mean length19.109218
Min length1

Characters and Unicode

Total characters338730
Distinct characters58
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4397 ?
Unique (%)24.8%

Sample

1st rowSEM LAUDO
2nd rowOPACIDADES
3rd rowATELECTASIA
4th rowESPESSAMENTO PERIBRONQUICO
5th rowINFILTRADO RETICULAR
ValueCountFrequency (%)
infiltrado 1748
 
4.1%
opacidade 1674
 
3.9%
de 1386
 
3.2%
sem 1265
 
2.9%
laudo 1140
 
2.7%
em 1020
 
2.4%
derrame 947
 
2.2%
arcos 936
 
2.2%
atelectasia 928
 
2.2%
pleural 908
 
2.1%
Other values (3016) 30940
72.1%
2023-09-22T21:41:52.245408image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 44258
13.1%
E 33147
 
9.8%
I 28893
 
8.5%
O 28446
 
8.4%
25252
 
7.5%
R 23070
 
6.8%
S 19519
 
5.8%
D 19205
 
5.7%
C 18531
 
5.5%
T 15362
 
4.5%
Other values (48) 83047
24.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 310580
91.7%
Space Separator 25257
 
7.5%
Other Punctuation 1823
 
0.5%
Decimal Number 428
 
0.1%
Dash Punctuation 289
 
0.1%
Math Symbol 275
 
0.1%
Open Punctuation 41
 
< 0.1%
Close Punctuation 35
 
< 0.1%
Modifier Symbol 1
 
< 0.1%
Other Letter 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 44258
14.3%
E 33147
10.7%
I 28893
9.3%
O 28446
9.2%
R 23070
 
7.4%
S 19519
 
6.3%
D 19205
 
6.2%
C 18531
 
6.0%
T 15362
 
4.9%
L 15288
 
4.9%
Other values (16) 64861
20.9%
Other Punctuation
ValueCountFrequency (%)
. 810
44.4%
, 473
25.9%
/ 285
 
15.6%
: 65
 
3.6%
; 65
 
3.6%
? 53
 
2.9%
" 49
 
2.7%
' 12
 
0.7%
¿ 5
 
0.3%
% 3
 
0.2%
Decimal Number
ValueCountFrequency (%)
2 92
21.5%
0 92
21.5%
3 89
20.8%
1 68
15.9%
8 23
 
5.4%
7 22
 
5.1%
6 14
 
3.3%
4 11
 
2.6%
5 11
 
2.6%
9 6
 
1.4%
Math Symbol
ValueCountFrequency (%)
+ 266
96.7%
> 4
 
1.5%
= 3
 
1.1%
~ 2
 
0.7%
Space Separator
ValueCountFrequency (%)
25252
> 99.9%
  5
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 289
100.0%
Open Punctuation
ValueCountFrequency (%)
( 41
100.0%
Close Punctuation
ValueCountFrequency (%)
) 35
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Other Letter
ValueCountFrequency (%)
º 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 310581
91.7%
Common 28149
 
8.3%

Most frequent character per script

Common
ValueCountFrequency (%)
25252
89.7%
. 810
 
2.9%
, 473
 
1.7%
- 289
 
1.0%
/ 285
 
1.0%
+ 266
 
0.9%
2 92
 
0.3%
0 92
 
0.3%
3 89
 
0.3%
1 68
 
0.2%
Other values (21) 433
 
1.5%
Latin
ValueCountFrequency (%)
A 44258
14.3%
E 33147
10.7%
I 28893
9.3%
O 28446
9.2%
R 23070
 
7.4%
S 19519
 
6.3%
D 19205
 
6.2%
C 18531
 
6.0%
T 15362
 
4.9%
L 15288
 
4.9%
Other values (17) 64862
20.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 338719
> 99.9%
None 11
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 44258
13.1%
E 33147
 
9.8%
I 28893
 
8.5%
O 28446
 
8.4%
25252
 
7.5%
R 23070
 
6.8%
S 19519
 
5.8%
D 19205
 
5.7%
C 18531
 
5.5%
T 15362
 
4.5%
Other values (45) 83036
24.5%
None
ValueCountFrequency (%)
¿ 5
45.5%
  5
45.5%
º 1
 
9.1%

DT_RAIOX
Text

MISSING 

Distinct305
Distinct (%)0.4%
Missing152609
Missing (%)64.8%
Memory size10.0 MiB
2023-09-22T21:41:52.630297image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9994583
Min length1

Characters and Unicode

Total characters830685
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)< 0.1%

Sample

1st row18/01/2023
2nd row02/01/2023
3rd row05/02/2023
4th row27/01/2023
5th row09/01/2023
ValueCountFrequency (%)
23/05/2023 571
 
0.7%
22/05/2023 549
 
0.7%
24/05/2023 547
 
0.7%
24/04/2023 539
 
0.6%
30/05/2023 529
 
0.6%
16/05/2023 524
 
0.6%
29/05/2023 520
 
0.6%
28/03/2023 519
 
0.6%
08/05/2023 515
 
0.6%
18/04/2023 515
 
0.6%
Other values (295) 77745
93.6%
2023-09-22T21:41:53.483580image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 209104
25.2%
0 198566
23.9%
/ 166136
20.0%
3 106716
12.8%
1 43328
 
5.2%
5 22156
 
2.7%
4 20654
 
2.5%
6 19754
 
2.4%
7 17715
 
2.1%
8 16386
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 664549
80.0%
Other Punctuation 166136
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 209104
31.5%
0 198566
29.9%
3 106716
16.1%
1 43328
 
6.5%
5 22156
 
3.3%
4 20654
 
3.1%
6 19754
 
3.0%
7 17715
 
2.7%
8 16386
 
2.5%
9 10170
 
1.5%
Other Punctuation
ValueCountFrequency (%)
/ 166136
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 830685
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 209104
25.2%
0 198566
23.9%
/ 166136
20.0%
3 106716
12.8%
1 43328
 
5.2%
5 22156
 
2.7%
4 20654
 
2.5%
6 19754
 
2.4%
7 17715
 
2.1%
8 16386
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 830685
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 209104
25.2%
0 198566
23.9%
/ 166136
20.0%
3 106716
12.8%
1 43328
 
5.2%
5 22156
 
2.7%
4 20654
 
2.5%
6 19754
 
2.4%
7 17715
 
2.1%
8 16386
 
2.0%

AMOSTRA
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct6
Distinct (%)< 0.1%
Missing8244
Missing (%)3.5%
Memory size12.9 MiB
1
217495 
2
 
9433
9
 
507
4
 
1
24/08/2023
 
1

Length

Max length10
Median length1
Mean length1.0000791
Min length1

Characters and Unicode

Total characters227456
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row2
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 217495
92.3%
2 9433
 
4.0%
9 507
 
0.2%
4 1
 
< 0.1%
24/08/2023 1
 
< 0.1%
03/08/2023 1
 
< 0.1%
(Missing) 8244
 
3.5%

Length

2023-09-22T21:41:53.894629image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:54.279526image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1 217495
95.6%
2 9433
 
4.1%
9 507
 
0.2%
4 1
 
< 0.1%
24/08/2023 1
 
< 0.1%
03/08/2023 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
1 217495
95.6%
2 9438
 
4.1%
9 507
 
0.2%
0 5
 
< 0.1%
/ 4
 
< 0.1%
3 3
 
< 0.1%
4 2
 
< 0.1%
8 2
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 227452
> 99.9%
Other Punctuation 4
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 217495
95.6%
2 9438
 
4.1%
9 507
 
0.2%
0 5
 
< 0.1%
3 3
 
< 0.1%
4 2
 
< 0.1%
8 2
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
/ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 227456
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 217495
95.6%
2 9438
 
4.1%
9 507
 
0.2%
0 5
 
< 0.1%
/ 4
 
< 0.1%
3 3
 
< 0.1%
4 2
 
< 0.1%
8 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 227456
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 217495
95.6%
2 9438
 
4.1%
9 507
 
0.2%
0 5
 
< 0.1%
/ 4
 
< 0.1%
3 3
 
< 0.1%
4 2
 
< 0.1%
8 2
 
< 0.1%

DT_COLETA
Text

MISSING 

Distinct272
Distinct (%)0.1%
Missing18180
Missing (%)7.7%
Memory size14.5 MiB
2023-09-22T21:41:54.687143image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9997931
Min length1

Characters and Unicode

Total characters2174975
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)< 0.1%

Sample

1st row03/01/2023
2nd row07/01/2023
3rd row24/01/2023
4th row05/02/2023
5th row04/02/2023
ValueCountFrequency (%)
24/04/2023 1497
 
0.7%
22/05/2023 1493
 
0.7%
02/05/2023 1460
 
0.7%
23/05/2023 1444
 
0.7%
10/04/2023 1430
 
0.7%
17/04/2023 1426
 
0.7%
29/05/2023 1405
 
0.6%
08/05/2023 1397
 
0.6%
15/05/2023 1395
 
0.6%
27/03/2023 1374
 
0.6%
Other values (262) 203181
93.4%
2023-09-22T21:41:55.163979image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 548394
25.2%
0 520537
23.9%
/ 434994
20.0%
3 281504
12.9%
1 116970
 
5.4%
5 57109
 
2.6%
4 53768
 
2.5%
6 50795
 
2.3%
7 44356
 
2.0%
8 39821
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1739981
80.0%
Other Punctuation 434994
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 548394
31.5%
0 520537
29.9%
3 281504
16.2%
1 116970
 
6.7%
5 57109
 
3.3%
4 53768
 
3.1%
6 50795
 
2.9%
7 44356
 
2.5%
8 39821
 
2.3%
9 26727
 
1.5%
Other Punctuation
ValueCountFrequency (%)
/ 434994
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2174975
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 548394
25.2%
0 520537
23.9%
/ 434994
20.0%
3 281504
12.9%
1 116970
 
5.4%
5 57109
 
2.6%
4 53768
 
2.5%
6 50795
 
2.3%
7 44356
 
2.0%
8 39821
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2174975
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 548394
25.2%
0 520537
23.9%
/ 434994
20.0%
3 281504
12.9%
1 116970
 
5.4%
5 57109
 
2.6%
4 53768
 
2.5%
6 50795
 
2.3%
7 44356
 
2.0%
8 39821
 
1.8%

TP_AMOSTRA
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct8
Distinct (%)< 0.1%
Missing23014
Missing (%)9.8%
Memory size12.6 MiB
1
200112 
4
 
11122
2
 
1011
9
 
326
3
 
79
Other values (3)
 
18

Length

Max length10
Median length1
Mean length1.0000423
Min length1

Characters and Unicode

Total characters212677
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row4
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 200112
84.9%
4 11122
 
4.7%
2 1011
 
0.4%
9 326
 
0.1%
3 79
 
< 0.1%
5 16
 
< 0.1%
26/05/2023 1
 
< 0.1%
0 1
 
< 0.1%
(Missing) 23014
 
9.8%

Length

2023-09-22T21:41:55.357443image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:55.551448image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1 200112
94.1%
4 11122
 
5.2%
2 1011
 
0.5%
9 326
 
0.2%
3 79
 
< 0.1%
5 16
 
< 0.1%
26/05/2023 1
 
< 0.1%
0 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
1 200112
94.1%
4 11122
 
5.2%
2 1014
 
0.5%
9 326
 
0.2%
3 80
 
< 0.1%
5 17
 
< 0.1%
0 3
 
< 0.1%
/ 2
 
< 0.1%
6 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 212675
> 99.9%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 200112
94.1%
4 11122
 
5.2%
2 1014
 
0.5%
9 326
 
0.2%
3 80
 
< 0.1%
5 17
 
< 0.1%
0 3
 
< 0.1%
6 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
/ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 212677
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 200112
94.1%
4 11122
 
5.2%
2 1014
 
0.5%
9 326
 
0.2%
3 80
 
< 0.1%
5 17
 
< 0.1%
0 3
 
< 0.1%
/ 2
 
< 0.1%
6 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 212677
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 200112
94.1%
4 11122
 
5.2%
2 1014
 
0.5%
9 326
 
0.2%
3 80
 
< 0.1%
5 17
 
< 0.1%
0 3
 
< 0.1%
/ 2
 
< 0.1%
6 1
 
< 0.1%

OUT_AMOST
Text

MISSING 

Distinct318
Distinct (%)3.0%
Missing225163
Missing (%)95.5%
Memory size7.6 MiB
2023-09-22T21:41:55.857806image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length30
Median length28
Mean length14.287575
Min length1

Characters and Unicode

Total characters150291
Distinct characters42
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique166 ?
Unique (%)1.6%

Sample

1st rowTR
2nd rowNASOFARINGE
3rd rowSECRECAO NASOFARINGE
4th rowNASOFARINGE
5th rowNASOFARINGE
ValueCountFrequency (%)
nasofaringe 5574
30.6%
swab 3044
16.7%
secrecao 1518
 
8.3%
nasofaringeo 1192
 
6.6%
teste 1173
 
6.4%
rapido 1140
 
6.3%
de 701
 
3.9%
nasofaringea 552
 
3.0%
aspirado 524
 
2.9%
antigeno 510
 
2.8%
Other values (245) 2265
12.4%
2023-09-22T21:41:56.384080image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 25094
16.7%
N 16815
11.2%
S 14748
9.8%
E 14720
9.8%
O 13392
8.9%
R 11906
7.9%
I 10158
6.8%
G 8210
 
5.5%
7681
 
5.1%
F 7516
 
5.0%
Other values (32) 20051
13.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 142292
94.7%
Space Separator 7681
 
5.1%
Other Punctuation 127
 
0.1%
Dash Punctuation 87
 
0.1%
Decimal Number 43
 
< 0.1%
Open Punctuation 29
 
< 0.1%
Close Punctuation 29
 
< 0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 25094
17.6%
N 16815
11.8%
S 14748
10.4%
E 14720
10.3%
O 13392
9.4%
R 11906
8.4%
I 10158
7.1%
G 8210
 
5.8%
F 7516
 
5.3%
T 3754
 
2.6%
Other values (14) 15979
11.2%
Decimal Number
ValueCountFrequency (%)
2 14
32.6%
1 9
20.9%
0 7
16.3%
9 5
 
11.6%
3 4
 
9.3%
4 2
 
4.7%
6 1
 
2.3%
5 1
 
2.3%
Other Punctuation
ValueCountFrequency (%)
. 76
59.8%
/ 39
30.7%
, 11
 
8.7%
? 1
 
0.8%
Math Symbol
ValueCountFrequency (%)
+ 2
66.7%
= 1
33.3%
Space Separator
ValueCountFrequency (%)
7681
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 87
100.0%
Open Punctuation
ValueCountFrequency (%)
( 29
100.0%
Close Punctuation
ValueCountFrequency (%)
) 29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 142292
94.7%
Common 7999
 
5.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 25094
17.6%
N 16815
11.8%
S 14748
10.4%
E 14720
10.3%
O 13392
9.4%
R 11906
8.4%
I 10158
7.1%
G 8210
 
5.8%
F 7516
 
5.3%
T 3754
 
2.6%
Other values (14) 15979
11.2%
Common
ValueCountFrequency (%)
7681
96.0%
- 87
 
1.1%
. 76
 
1.0%
/ 39
 
0.5%
( 29
 
0.4%
) 29
 
0.4%
2 14
 
0.2%
, 11
 
0.1%
1 9
 
0.1%
0 7
 
0.1%
Other values (8) 17
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 150291
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 25094
16.7%
N 16815
11.2%
S 14748
9.8%
E 14720
9.8%
O 13392
8.9%
R 11906
7.9%
I 10158
6.8%
G 8210
 
5.5%
7681
 
5.1%
F 7516
 
5.0%
Other values (32) 20051
13.3%

PCR_RESUL
Categorical

HIGH CORRELATION  MISSING 

Distinct8
Distinct (%)< 0.1%
Missing21350
Missing (%)9.1%
Memory size12.7 MiB
2
84920 
1
63116 
5
35347 
4
29769 
9
 
943
Other values (3)
 
237

Length

Max length10
Median length1
Mean length1.000084
Min length1

Characters and Unicode

Total characters214350
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row5
2nd row4
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 84920
36.0%
1 63116
26.8%
5 35347
15.0%
4 29769
 
12.6%
9 943
 
0.4%
3 235
 
0.1%
31/07/2023 1
 
< 0.1%
19/05/2021 1
 
< 0.1%
(Missing) 21350
 
9.1%

Length

2023-09-22T21:41:56.567791image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:56.765256image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
2 84920
39.6%
1 63116
29.4%
5 35347
16.5%
4 29769
 
13.9%
9 943
 
0.4%
3 235
 
0.1%
31/07/2023 1
 
< 0.1%
19/05/2021 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
2 84924
39.6%
1 63119
29.4%
5 35348
16.5%
4 29769
 
13.9%
9 944
 
0.4%
3 237
 
0.1%
/ 4
 
< 0.1%
0 4
 
< 0.1%
7 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 214346
> 99.9%
Other Punctuation 4
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 84924
39.6%
1 63119
29.4%
5 35348
16.5%
4 29769
 
13.9%
9 944
 
0.4%
3 237
 
0.1%
0 4
 
< 0.1%
7 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
/ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 214350
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 84924
39.6%
1 63119
29.4%
5 35348
16.5%
4 29769
 
13.9%
9 944
 
0.4%
3 237
 
0.1%
/ 4
 
< 0.1%
0 4
 
< 0.1%
7 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 214350
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 84924
39.6%
1 63119
29.4%
5 35348
16.5%
4 29769
 
13.9%
9 944
 
0.4%
3 237
 
0.1%
/ 4
 
< 0.1%
0 4
 
< 0.1%
7 1
 
< 0.1%

DT_PCR
Text

MISSING 

Distinct263
Distinct (%)0.2%
Missing87355
Missing (%)37.1%
Memory size12.1 MiB
2023-09-22T21:41:57.107424image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length49
Median length10
Mean length10.000142
Min length1

Characters and Unicode

Total characters1483291
Distinct characters13
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st row31/01/2023
2nd row06/02/2023
3rd row08/02/2023
4th row04/02/2023
5th row18/01/2023
ValueCountFrequency (%)
07/06/2023 1283
 
0.9%
30/05/2023 1223
 
0.8%
18/05/2023 1211
 
0.8%
25/05/2023 1188
 
0.8%
02/06/2023 1119
 
0.8%
20/04/2023 1108
 
0.7%
23/05/2023 1093
 
0.7%
11/04/2023 1067
 
0.7%
14/04/2023 1061
 
0.7%
29/03/2023 1048
 
0.7%
Other values (253) 136926
92.3%
2023-09-22T21:41:57.635246image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 371801
25.1%
0 353866
23.9%
/ 296652
20.0%
3 192624
13.0%
1 77929
 
5.3%
5 40050
 
2.7%
6 36843
 
2.5%
4 36512
 
2.5%
7 32645
 
2.2%
8 27607
 
1.9%
Other values (3) 16762
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1186612
80.0%
Other Punctuation 296679
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 371801
31.3%
0 353866
29.8%
3 192624
16.2%
1 77929
 
6.6%
5 40050
 
3.4%
6 36843
 
3.1%
4 36512
 
3.1%
7 32645
 
2.8%
8 27607
 
2.3%
9 16735
 
1.4%
Other Punctuation
ValueCountFrequency (%)
/ 296652
> 99.9%
; 23
 
< 0.1%
" 4
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 1483291
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 371801
25.1%
0 353866
23.9%
/ 296652
20.0%
3 192624
13.0%
1 77929
 
5.3%
5 40050
 
2.7%
6 36843
 
2.5%
4 36512
 
2.5%
7 32645
 
2.2%
8 27607
 
1.9%
Other values (3) 16762
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1483291
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 371801
25.1%
0 353866
23.9%
/ 296652
20.0%
3 192624
13.0%
1 77929
 
5.3%
5 40050
 
2.7%
6 36843
 
2.5%
4 36512
 
2.5%
7 32645
 
2.2%
8 27607
 
1.9%
Other values (3) 16762
 
1.1%

POS_PCRFLU
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct5
Distinct (%)< 0.1%
Missing181183
Missing (%)76.9%
Memory size9.9 MiB
2
44420 
1
9446 
9
 
631
0
 
1
06/03/2021
 
1

Length

Max length10
Median length1
Mean length1.0001651
Min length1

Characters and Unicode

Total characters54508
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row2
2nd row9
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 44420
 
18.8%
1 9446
 
4.0%
9 631
 
0.3%
0 1
 
< 0.1%
06/03/2021 1
 
< 0.1%
(Missing) 181183
76.9%

Length

2023-09-22T21:41:57.853978image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:58.024658image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
2 44420
81.5%
1 9446
 
17.3%
9 631
 
1.2%
0 1
 
< 0.1%
06/03/2021 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
2 44422
81.5%
1 9447
 
17.3%
9 631
 
1.2%
0 4
 
< 0.1%
/ 2
 
< 0.1%
6 1
 
< 0.1%
3 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 54506
> 99.9%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 44422
81.5%
1 9447
 
17.3%
9 631
 
1.2%
0 4
 
< 0.1%
6 1
 
< 0.1%
3 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
/ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 54508
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 44422
81.5%
1 9447
 
17.3%
9 631
 
1.2%
0 4
 
< 0.1%
/ 2
 
< 0.1%
6 1
 
< 0.1%
3 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 54508
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 44422
81.5%
1 9447
 
17.3%
9 631
 
1.2%
0 4
 
< 0.1%
/ 2
 
< 0.1%
6 1
 
< 0.1%
3 1
 
< 0.1%

TP_FLU_PCR
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct4
Distinct (%)< 0.1%
Missing226238
Missing (%)96.0%
Memory size9.2 MiB
1
5862 
2
3580 
85 - COVID-19 ASTRAZENECA/FIOCRUZ - COVISHIELD
 
1
08/03/2023
 
1

Length

Max length46
Median length1
Mean length1.0057179
Min length1

Characters and Unicode

Total characters9498
Distinct characters26
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row1
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
1 5862
 
2.5%
2 3580
 
1.5%
85 - COVID-19 ASTRAZENECA/FIOCRUZ - COVISHIELD 1
 
< 0.1%
08/03/2023 1
 
< 0.1%
(Missing) 226238
96.0%

Length

2023-09-22T21:41:58.177463image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:58.358534image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1 5862
62.0%
2 3580
37.9%
2
 
< 0.1%
85 1
 
< 0.1%
covid-19 1
 
< 0.1%
astrazeneca/fiocruz 1
 
< 0.1%
covishield 1
 
< 0.1%
08/03/2023 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
1 5863
61.7%
2 3582
37.7%
5
 
0.1%
C 4
 
< 0.1%
I 4
 
< 0.1%
0 3
 
< 0.1%
/ 3
 
< 0.1%
- 3
 
< 0.1%
O 3
 
< 0.1%
E 3
 
< 0.1%
Other values (16) 25
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9454
99.5%
Uppercase Letter 33
 
0.3%
Space Separator 5
 
0.1%
Other Punctuation 3
 
< 0.1%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 4
12.1%
I 4
12.1%
O 3
9.1%
E 3
9.1%
A 3
9.1%
Z 2
 
6.1%
R 2
 
6.1%
S 2
 
6.1%
D 2
 
6.1%
V 2
 
6.1%
Other values (6) 6
18.2%
Decimal Number
ValueCountFrequency (%)
1 5863
62.0%
2 3582
37.9%
0 3
 
< 0.1%
8 2
 
< 0.1%
3 2
 
< 0.1%
9 1
 
< 0.1%
5 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
5
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9465
99.7%
Latin 33
 
0.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
C 4
12.1%
I 4
12.1%
O 3
9.1%
E 3
9.1%
A 3
9.1%
Z 2
 
6.1%
R 2
 
6.1%
S 2
 
6.1%
D 2
 
6.1%
V 2
 
6.1%
Other values (6) 6
18.2%
Common
ValueCountFrequency (%)
1 5863
61.9%
2 3582
37.8%
5
 
0.1%
0 3
 
< 0.1%
/ 3
 
< 0.1%
- 3
 
< 0.1%
8 2
 
< 0.1%
3 2
 
< 0.1%
9 1
 
< 0.1%
5 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9498
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 5863
61.7%
2 3582
37.7%
5
 
0.1%
C 4
 
< 0.1%
I 4
 
< 0.1%
0 3
 
< 0.1%
/ 3
 
< 0.1%
- 3
 
< 0.1%
O 3
 
< 0.1%
E 3
 
< 0.1%
Other values (16) 25
 
0.3%

PCR_FLUASU
Categorical

HIGH CORRELATION  MISSING 

Distinct8
Distinct (%)0.1%
Missing229816
Missing (%)97.5%
Memory size9.1 MiB
1
3208 
3
2001 
4
330 
5
 
209
6
 
71
Other values (3)
 
47

Length

Max length46
Median length1
Mean length1.0146608
Min length1

Characters and Unicode

Total characters5952
Distinct characters28
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row4
2nd row1
3rd row3
4th row1
5th row3

Common Values

ValueCountFrequency (%)
1 3208
 
1.4%
3 2001
 
0.8%
4 330
 
0.1%
5 209
 
0.1%
6 71
 
< 0.1%
2 45
 
< 0.1%
85 - COVID-19 ASTRAZENECA/FIOCRUZ - COVISHIELD 1
 
< 0.1%
86 - COVID-19 SINOVAC/BUTANTAN - CORONAVAC 1
 
< 0.1%
(Missing) 229816
97.5%

Length

2023-09-22T21:41:58.518109image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:58.712665image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1 3208
54.6%
3 2001
34.1%
4 330
 
5.6%
5 209
 
3.6%
6 71
 
1.2%
2 45
 
0.8%
4
 
0.1%
covid-19 2
 
< 0.1%
85 1
 
< 0.1%
astrazeneca/fiocruz 1
 
< 0.1%
Other values (4) 4
 
0.1%

Most occurring characters

ValueCountFrequency (%)
1 3210
53.9%
3 2001
33.6%
4 330
 
5.5%
5 210
 
3.5%
6 72
 
1.2%
2 45
 
0.8%
10
 
0.2%
C 8
 
0.1%
A 8
 
0.1%
O 7
 
0.1%
Other values (18) 51
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5872
98.7%
Uppercase Letter 62
 
1.0%
Space Separator 10
 
0.2%
Dash Punctuation 6
 
0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 8
12.9%
A 8
12.9%
O 7
11.3%
I 6
9.7%
N 5
8.1%
V 5
8.1%
D 3
 
4.8%
S 3
 
4.8%
T 3
 
4.8%
R 3
 
4.8%
Other values (7) 11
17.7%
Decimal Number
ValueCountFrequency (%)
1 3210
54.7%
3 2001
34.1%
4 330
 
5.6%
5 210
 
3.6%
6 72
 
1.2%
2 45
 
0.8%
9 2
 
< 0.1%
8 2
 
< 0.1%
Space Separator
ValueCountFrequency (%)
10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5890
99.0%
Latin 62
 
1.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
C 8
12.9%
A 8
12.9%
O 7
11.3%
I 6
9.7%
N 5
8.1%
V 5
8.1%
D 3
 
4.8%
S 3
 
4.8%
T 3
 
4.8%
R 3
 
4.8%
Other values (7) 11
17.7%
Common
ValueCountFrequency (%)
1 3210
54.5%
3 2001
34.0%
4 330
 
5.6%
5 210
 
3.6%
6 72
 
1.2%
2 45
 
0.8%
10
 
0.2%
- 6
 
0.1%
/ 2
 
< 0.1%
9 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3210
53.9%
3 2001
33.6%
4 330
 
5.5%
5 210
 
3.5%
6 72
 
1.2%
2 45
 
0.8%
10
 
0.2%
C 8
 
0.1%
A 8
 
0.1%
O 7
 
0.1%
Other values (18) 51
 
0.9%

FLUASU_OUT
Text

MISSING 

Distinct27
Distinct (%)51.9%
Missing235630
Missing (%)> 99.9%
Memory size7.2 MiB
2023-09-22T21:41:58.961545image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length42
Median length26
Mean length15.461538
Min length1

Characters and Unicode

Total characters804
Distinct characters34
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)30.8%

Sample

1st rowNAO ESPECIFICADO
2nd rowINF A SAZONAL /H1
3rd rowNAO SUBTIPADO
4th row1
5th rowNAO INFORMADO NO LAUDO
ValueCountFrequency (%)
nao 27
20.9%
influenza 10
 
7.8%
a 10
 
7.8%
informado 9
 
7.0%
realizado 7
 
5.4%
laudo 6
 
4.7%
sazonal/h1 5
 
3.9%
subtipado 4
 
3.1%
especificado 4
 
3.1%
sazonal 4
 
3.1%
Other values (36) 43
33.3%
2023-09-22T21:41:59.406996image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 118
14.7%
O 92
11.4%
N 84
 
10.4%
78
 
9.7%
I 52
 
6.5%
E 38
 
4.7%
L 37
 
4.6%
D 32
 
4.0%
U 28
 
3.5%
Z 27
 
3.4%
Other values (24) 218
27.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 668
83.1%
Space Separator 78
 
9.7%
Decimal Number 36
 
4.5%
Other Punctuation 16
 
2.0%
Dash Punctuation 4
 
0.5%
Close Punctuation 2
 
0.2%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 118
17.7%
O 92
13.8%
N 84
12.6%
I 52
 
7.8%
E 38
 
5.7%
L 37
 
5.5%
D 32
 
4.8%
U 28
 
4.2%
Z 27
 
4.0%
F 26
 
3.9%
Other values (10) 134
20.1%
Decimal Number
ValueCountFrequency (%)
1 16
44.4%
2 6
 
16.7%
3 4
 
11.1%
0 4
 
11.1%
9 3
 
8.3%
8 1
 
2.8%
6 1
 
2.8%
5 1
 
2.8%
Other Punctuation
ValueCountFrequency (%)
/ 13
81.2%
, 2
 
12.5%
. 1
 
6.2%
Space Separator
ValueCountFrequency (%)
78
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 668
83.1%
Common 136
 
16.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 118
17.7%
O 92
13.8%
N 84
12.6%
I 52
 
7.8%
E 38
 
5.7%
L 37
 
5.5%
D 32
 
4.8%
U 28
 
4.2%
Z 27
 
4.0%
F 26
 
3.9%
Other values (10) 134
20.1%
Common
ValueCountFrequency (%)
78
57.4%
1 16
 
11.8%
/ 13
 
9.6%
2 6
 
4.4%
3 4
 
2.9%
- 4
 
2.9%
0 4
 
2.9%
9 3
 
2.2%
) 2
 
1.5%
, 2
 
1.5%
Other values (4) 4
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 804
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 118
14.7%
O 92
11.4%
N 84
 
10.4%
78
 
9.7%
I 52
 
6.5%
E 38
 
4.7%
L 37
 
4.6%
D 32
 
4.0%
U 28
 
3.5%
Z 27
 
3.4%
Other values (24) 218
27.1%

PCR_FLUBLI
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct7
Distinct (%)0.3%
Missing233511
Missing (%)99.1%
Memory size9.0 MiB
3
1840 
1
234 
4
 
69
5
 
24
2
 
2
Other values (2)
 
2

Length

Max length46
Median length1
Mean length1.0400737
Min length1

Characters and Unicode

Total characters2258
Distinct characters31
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st row3
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 1840
 
0.8%
1 234
 
0.1%
4 69
 
< 0.1%
5 24
 
< 0.1%
2 2
 
< 0.1%
85 - COVID-19 ASTRAZENECA/FIOCRUZ - COVISHIELD 1
 
< 0.1%
103 - COVID-19 PFIZER - COMIRNATY BIVALENTE 1
 
< 0.1%
(Missing) 233511
99.1%

Length

2023-09-22T21:41:59.602672image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:41:59.807642image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
3 1840
84.3%
1 234
 
10.7%
4 69
 
3.2%
5 24
 
1.1%
4
 
0.2%
2 2
 
0.1%
covid-19 2
 
0.1%
85 1
 
< 0.1%
astrazeneca/fiocruz 1
 
< 0.1%
covishield 1
 
< 0.1%
Other values (4) 4
 
0.2%

Most occurring characters

ValueCountFrequency (%)
3 1841
81.5%
1 237
 
10.5%
4 69
 
3.1%
5 25
 
1.1%
11
 
0.5%
I 8
 
0.4%
- 6
 
0.3%
C 6
 
0.3%
E 6
 
0.3%
A 5
 
0.2%
Other values (21) 44
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2178
96.5%
Uppercase Letter 62
 
2.7%
Space Separator 11
 
0.5%
Dash Punctuation 6
 
0.3%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
I 8
12.9%
C 6
 
9.7%
E 6
 
9.7%
A 5
 
8.1%
O 5
 
8.1%
V 4
 
6.5%
R 4
 
6.5%
D 3
 
4.8%
N 3
 
4.8%
T 3
 
4.8%
Other values (10) 15
24.2%
Decimal Number
ValueCountFrequency (%)
3 1841
84.5%
1 237
 
10.9%
4 69
 
3.2%
5 25
 
1.1%
9 2
 
0.1%
2 2
 
0.1%
8 1
 
< 0.1%
0 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2196
97.3%
Latin 62
 
2.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
I 8
12.9%
C 6
 
9.7%
E 6
 
9.7%
A 5
 
8.1%
O 5
 
8.1%
V 4
 
6.5%
R 4
 
6.5%
D 3
 
4.8%
N 3
 
4.8%
T 3
 
4.8%
Other values (10) 15
24.2%
Common
ValueCountFrequency (%)
3 1841
83.8%
1 237
 
10.8%
4 69
 
3.1%
5 25
 
1.1%
11
 
0.5%
- 6
 
0.3%
9 2
 
0.1%
2 2
 
0.1%
/ 1
 
< 0.1%
8 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2258
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 1841
81.5%
1 237
 
10.5%
4 69
 
3.1%
5 25
 
1.1%
11
 
0.5%
I 8
 
0.4%
- 6
 
0.3%
C 6
 
0.3%
E 6
 
0.3%
A 5
 
0.2%
Other values (21) 44
 
1.9%

FLUBLI_OUT
Text

MISSING 

Distinct9
Distinct (%)75.0%
Missing235670
Missing (%)> 99.9%
Memory size7.2 MiB
2023-09-22T21:42:00.036626image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length42
Median length19
Mean length13
Min length1

Characters and Unicode

Total characters156
Distinct characters31
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)66.7%

Sample

1st row214VCD067Z
2nd rowIN HOUSE
3rd row2
4th row86 - COVID-19 SINOVAC/BUTANTAN - CORONAVAC
5th rowIN HOUSE
ValueCountFrequency (%)
in 4
16.7%
house 4
16.7%
nao 3
12.5%
2
 
8.3%
214vcd067z 1
 
4.2%
2 1
 
4.2%
86 1
 
4.2%
covid-19 1
 
4.2%
sinovac/butantan 1
 
4.2%
coronavac 1
 
4.2%
Other values (5) 5
20.8%
2023-09-22T21:42:00.443603image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 17
 
10.9%
O 14
 
9.0%
12
 
7.7%
N 12
 
7.7%
I 11
 
7.1%
S 9
 
5.8%
U 7
 
4.5%
C 7
 
4.5%
E 7
 
4.5%
D 5
 
3.2%
Other values (21) 55
35.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 115
73.7%
Decimal Number 22
 
14.1%
Space Separator 12
 
7.7%
Other Punctuation 4
 
2.6%
Dash Punctuation 3
 
1.9%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 17
14.8%
O 14
12.2%
N 12
10.4%
I 11
9.6%
S 9
7.8%
U 7
 
6.1%
C 7
 
6.1%
E 7
 
6.1%
D 5
 
4.3%
H 4
 
3.5%
Other values (8) 22
19.1%
Decimal Number
ValueCountFrequency (%)
1 5
22.7%
2 4
18.2%
6 2
 
9.1%
9 2
 
9.1%
7 2
 
9.1%
0 2
 
9.1%
4 2
 
9.1%
8 1
 
4.5%
3 1
 
4.5%
5 1
 
4.5%
Space Separator
ValueCountFrequency (%)
12
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 115
73.7%
Common 41
 
26.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 17
14.8%
O 14
12.2%
N 12
10.4%
I 11
9.6%
S 9
7.8%
U 7
 
6.1%
C 7
 
6.1%
E 7
 
6.1%
D 5
 
4.3%
H 4
 
3.5%
Other values (8) 22
19.1%
Common
ValueCountFrequency (%)
12
29.3%
1 5
12.2%
/ 4
 
9.8%
2 4
 
9.8%
- 3
 
7.3%
6 2
 
4.9%
9 2
 
4.9%
7 2
 
4.9%
0 2
 
4.9%
4 2
 
4.9%
Other values (3) 3
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 156
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 17
 
10.9%
O 14
 
9.0%
12
 
7.7%
N 12
 
7.7%
I 11
 
7.1%
S 9
 
5.8%
U 7
 
4.5%
C 7
 
4.5%
E 7
 
4.5%
D 5
 
3.2%
Other values (21) 55
35.3%

POS_PCROUT
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct5
Distinct (%)< 0.1%
Missing176255
Missing (%)74.8%
Memory size10.0 MiB
1
53006 
2
6376 
9
 
43
219VCD288Z
 
1
210010
 
1

Length

Max length10
Median length1
Mean length1.0002356
Min length1

Characters and Unicode

Total characters59441
Distinct characters9
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 53006
 
22.5%
2 6376
 
2.7%
9 43
 
< 0.1%
219VCD288Z 1
 
< 0.1%
210010 1
 
< 0.1%
(Missing) 176255
74.8%

Length

2023-09-22T21:42:00.641253image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:00.829575image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1 53006
89.2%
2 6376
 
10.7%
9 43
 
0.1%
219vcd288z 1
 
< 0.1%
210010 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
1 53009
89.2%
2 6379
 
10.7%
9 44
 
0.1%
0 3
 
< 0.1%
8 2
 
< 0.1%
V 1
 
< 0.1%
C 1
 
< 0.1%
D 1
 
< 0.1%
Z 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59437
> 99.9%
Uppercase Letter 4
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 53009
89.2%
2 6379
 
10.7%
9 44
 
0.1%
0 3
 
< 0.1%
8 2
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
V 1
25.0%
C 1
25.0%
D 1
25.0%
Z 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 59437
> 99.9%
Latin 4
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 53009
89.2%
2 6379
 
10.7%
9 44
 
0.1%
0 3
 
< 0.1%
8 2
 
< 0.1%
Latin
ValueCountFrequency (%)
V 1
25.0%
C 1
25.0%
D 1
25.0%
Z 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 59441
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 53009
89.2%
2 6379
 
10.7%
9 44
 
0.1%
0 3
 
< 0.1%
8 2
 
< 0.1%
V 1
 
< 0.1%
C 1
 
< 0.1%
D 1
 
< 0.1%
Z 1
 
< 0.1%

PCR_VSR
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct3
Distinct (%)< 0.1%
Missing212140
Missing (%)90.0%
Memory size9.4 MiB
1.0
23539 
2.0
 
2
210037.0
 
1

Length

Max length8
Median length3
Mean length3.0002124
Min length3

Characters and Unicode

Total characters70631
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 23539
 
10.0%
2.0 2
 
< 0.1%
210037.0 1
 
< 0.1%
(Missing) 212140
90.0%

Length

2023-09-22T21:42:01.002340image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:01.163749image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1.0 23539
> 99.9%
2.0 2
 
< 0.1%
210037.0 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 23544
33.3%
. 23542
33.3%
1 23540
33.3%
2 3
 
< 0.1%
3 1
 
< 0.1%
7 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 47089
66.7%
Other Punctuation 23542
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 23544
50.0%
1 23540
50.0%
2 3
 
< 0.1%
3 1
 
< 0.1%
7 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 23542
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 70631
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 23544
33.3%
. 23542
33.3%
1 23540
33.3%
2 3
 
< 0.1%
3 1
 
< 0.1%
7 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70631
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 23544
33.3%
. 23542
33.3%
1 23540
33.3%
2 3
 
< 0.1%
3 1
 
< 0.1%
7 1
 
< 0.1%

PCR_PARA1
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct3
Distinct (%)1.2%
Missing235435
Missing (%)99.9%
Memory size9.0 MiB
1
243 
2
 
3
GF9674
 
1

Length

Max length6
Median length1
Mean length1.0202429
Min length1

Characters and Unicode

Total characters252
Distinct characters8
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 243
 
0.1%
2 3
 
< 0.1%
GF9674 1
 
< 0.1%
(Missing) 235435
99.9%

Length

2023-09-22T21:42:01.315794image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:01.505678image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1 243
98.4%
2 3
 
1.2%
gf9674 1
 
0.4%

Most occurring characters

ValueCountFrequency (%)
1 243
96.4%
2 3
 
1.2%
G 1
 
0.4%
F 1
 
0.4%
9 1
 
0.4%
6 1
 
0.4%
7 1
 
0.4%
4 1
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 250
99.2%
Uppercase Letter 2
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 243
97.2%
2 3
 
1.2%
9 1
 
0.4%
6 1
 
0.4%
7 1
 
0.4%
4 1
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
G 1
50.0%
F 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 250
99.2%
Latin 2
 
0.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 243
97.2%
2 3
 
1.2%
9 1
 
0.4%
6 1
 
0.4%
7 1
 
0.4%
4 1
 
0.4%
Latin
ValueCountFrequency (%)
G 1
50.0%
F 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 252
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 243
96.4%
2 3
 
1.2%
G 1
 
0.4%
F 1
 
0.4%
9 1
 
0.4%
6 1
 
0.4%
7 1
 
0.4%
4 1
 
0.4%

PCR_PARA2
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct3
Distinct (%)2.6%
Missing235566
Missing (%)> 99.9%
Memory size9.0 MiB
1.0
112 
2.0
 
3
5.0
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters348
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.9%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 112
 
< 0.1%
2.0 3
 
< 0.1%
5.0 1
 
< 0.1%
(Missing) 235566
> 99.9%

Length

2023-09-22T21:42:01.647224image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:01.820955image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1.0 112
96.6%
2.0 3
 
2.6%
5.0 1
 
0.9%

Most occurring characters

ValueCountFrequency (%)
. 116
33.3%
0 116
33.3%
1 112
32.2%
2 3
 
0.9%
5 1
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 232
66.7%
Other Punctuation 116
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 116
50.0%
1 112
48.3%
2 3
 
1.3%
5 1
 
0.4%
Other Punctuation
ValueCountFrequency (%)
. 116
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 348
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 116
33.3%
0 116
33.3%
1 112
32.2%
2 3
 
0.9%
5 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 348
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 116
33.3%
0 116
33.3%
1 112
32.2%
2 3
 
0.9%
5 1
 
0.3%

PCR_PARA3
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct5
Distinct (%)0.4%
Missing234519
Missing (%)99.5%
Memory size9.0 MiB
1
1159 
30/05/2023
 
1
03/03/2021
 
1
29/03/2022
 
1
6
 
1

Length

Max length10
Median length1
Mean length1.0232158
Min length1

Characters and Unicode

Total characters1190
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)0.3%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 1159
 
0.5%
30/05/2023 1
 
< 0.1%
03/03/2021 1
 
< 0.1%
29/03/2022 1
 
< 0.1%
6 1
 
< 0.1%
(Missing) 234519
99.5%

Length

2023-09-22T21:42:01.967083image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:02.135783image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1 1159
99.7%
30/05/2023 1
 
0.1%
03/03/2021 1
 
0.1%
29/03/2022 1
 
0.1%
6 1
 
0.1%

Most occurring characters

ValueCountFrequency (%)
1 1160
97.5%
0 8
 
0.7%
2 8
 
0.7%
/ 6
 
0.5%
3 5
 
0.4%
5 1
 
0.1%
9 1
 
0.1%
6 1
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1184
99.5%
Other Punctuation 6
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1160
98.0%
0 8
 
0.7%
2 8
 
0.7%
3 5
 
0.4%
5 1
 
0.1%
9 1
 
0.1%
6 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
/ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1190
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1160
97.5%
0 8
 
0.7%
2 8
 
0.7%
/ 6
 
0.5%
3 5
 
0.4%
5 1
 
0.1%
9 1
 
0.1%
6 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1190
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1160
97.5%
0 8
 
0.7%
2 8
 
0.7%
/ 6
 
0.5%
3 5
 
0.4%
5 1
 
0.1%
9 1
 
0.1%
6 1
 
0.1%

PCR_PARA4
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct4
Distinct (%)5.7%
Missing235612
Missing (%)> 99.9%
Memory size9.0 MiB
1
67 
05/06/2023
 
1
08/06/2021
 
1
88 - COVID-19 JANSSEN - AD26.COV2.S
 
1

Length

Max length35
Median length1
Mean length1.7428571
Min length1

Characters and Unicode

Total characters122
Distinct characters22
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)4.3%

Sample

1st row1
2nd row1
3rd row05/06/2023
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 67
 
< 0.1%
05/06/2023 1
 
< 0.1%
08/06/2021 1
 
< 0.1%
88 - COVID-19 JANSSEN - AD26.COV2.S 1
 
< 0.1%
(Missing) 235612
> 99.9%

Length

2023-09-22T21:42:02.297407image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:02.510965image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1 67
89.3%
2
 
2.7%
05/06/2023 1
 
1.3%
08/06/2021 1
 
1.3%
88 1
 
1.3%
covid-19 1
 
1.3%
janssen 1
 
1.3%
ad26.cov2.s 1
 
1.3%

Most occurring characters

ValueCountFrequency (%)
1 69
56.6%
2 6
 
4.9%
0 6
 
4.9%
5
 
4.1%
/ 4
 
3.3%
S 3
 
2.5%
6 3
 
2.5%
8 3
 
2.5%
- 3
 
2.5%
D 2
 
1.6%
Other values (12) 18
 
14.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 90
73.8%
Uppercase Letter 18
 
14.8%
Other Punctuation 6
 
4.9%
Space Separator 5
 
4.1%
Dash Punctuation 3
 
2.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 3
16.7%
D 2
11.1%
N 2
11.1%
A 2
11.1%
O 2
11.1%
V 2
11.1%
C 2
11.1%
I 1
 
5.6%
J 1
 
5.6%
E 1
 
5.6%
Decimal Number
ValueCountFrequency (%)
1 69
76.7%
2 6
 
6.7%
0 6
 
6.7%
6 3
 
3.3%
8 3
 
3.3%
9 1
 
1.1%
3 1
 
1.1%
5 1
 
1.1%
Other Punctuation
ValueCountFrequency (%)
/ 4
66.7%
. 2
33.3%
Space Separator
ValueCountFrequency (%)
5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 104
85.2%
Latin 18
 
14.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 69
66.3%
2 6
 
5.8%
0 6
 
5.8%
5
 
4.8%
/ 4
 
3.8%
6 3
 
2.9%
8 3
 
2.9%
- 3
 
2.9%
. 2
 
1.9%
9 1
 
1.0%
Other values (2) 2
 
1.9%
Latin
ValueCountFrequency (%)
S 3
16.7%
D 2
11.1%
N 2
11.1%
A 2
11.1%
O 2
11.1%
V 2
11.1%
C 2
11.1%
I 1
 
5.6%
J 1
 
5.6%
E 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 122
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 69
56.6%
2 6
 
4.9%
0 6
 
4.9%
5
 
4.1%
/ 4
 
3.3%
S 3
 
2.5%
6 3
 
2.5%
8 3
 
2.5%
- 3
 
2.5%
D 2
 
1.6%
Other values (12) 18
 
14.8%

PCR_ADENO
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct6
Distinct (%)0.3%
Missing233929
Missing (%)99.3%
Memory size9.0 MiB
1
1748 
15/05/2023
 
1
9
 
1
27/04/2022
 
1
2
 
1

Length

Max length10
Median length1
Mean length1.0136908
Min length1

Characters and Unicode

Total characters1777
Distinct characters11
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)0.3%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 1748
 
0.7%
15/05/2023 1
 
< 0.1%
9 1
 
< 0.1%
27/04/2022 1
 
< 0.1%
2 1
 
< 0.1%
210F21A 1
 
< 0.1%
(Missing) 233929
99.3%

Length

2023-09-22T21:42:03.661070image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:03.858305image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1 1748
99.7%
15/05/2023 1
 
0.1%
9 1
 
0.1%
27/04/2022 1
 
0.1%
2 1
 
0.1%
210f21a 1
 
0.1%

Most occurring characters

ValueCountFrequency (%)
1 1751
98.5%
2 9
 
0.5%
0 5
 
0.3%
/ 4
 
0.2%
5 2
 
0.1%
3 1
 
0.1%
9 1
 
0.1%
7 1
 
0.1%
4 1
 
0.1%
F 1
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1771
99.7%
Other Punctuation 4
 
0.2%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1751
98.9%
2 9
 
0.5%
0 5
 
0.3%
5 2
 
0.1%
3 1
 
0.1%
9 1
 
0.1%
7 1
 
0.1%
4 1
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
F 1
50.0%
A 1
50.0%
Other Punctuation
ValueCountFrequency (%)
/ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1775
99.9%
Latin 2
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1751
98.6%
2 9
 
0.5%
0 5
 
0.3%
/ 4
 
0.2%
5 2
 
0.1%
3 1
 
0.1%
9 1
 
0.1%
7 1
 
0.1%
4 1
 
0.1%
Latin
ValueCountFrequency (%)
F 1
50.0%
A 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1777
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1751
98.5%
2 9
 
0.5%
0 5
 
0.3%
/ 4
 
0.2%
5 2
 
0.1%
3 1
 
0.1%
9 1
 
0.1%
7 1
 
0.1%
4 1
 
0.1%
F 1
 
0.1%

PCR_METAP
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct5
Distinct (%)0.2%
Missing233150
Missing (%)98.9%
Memory size9.0 MiB
1
2527 
2
 
2
0
 
1
85 - COVID-19 ASTRAZENECA/FIOCRUZ - COVISHIELD
 
1
09/03/2023
 
1

Length

Max length46
Median length1
Mean length1.021327
Min length1

Characters and Unicode

Total characters2586
Distinct characters26
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)0.1%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 2527
 
1.1%
2 2
 
< 0.1%
0 1
 
< 0.1%
85 - COVID-19 ASTRAZENECA/FIOCRUZ - COVISHIELD 1
 
< 0.1%
09/03/2023 1
 
< 0.1%
(Missing) 233150
98.9%

Length

2023-09-22T21:42:04.040041image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:04.213040image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1 2527
99.6%
2 2
 
0.1%
2
 
0.1%
0 1
 
< 0.1%
85 1
 
< 0.1%
covid-19 1
 
< 0.1%
astrazeneca/fiocruz 1
 
< 0.1%
covishield 1
 
< 0.1%
09/03/2023 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
1 2528
97.8%
5
 
0.2%
I 4
 
0.2%
0 4
 
0.2%
2 4
 
0.2%
C 4
 
0.2%
/ 3
 
0.1%
E 3
 
0.1%
A 3
 
0.1%
O 3
 
0.1%
Other values (16) 25
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2542
98.3%
Uppercase Letter 33
 
1.3%
Space Separator 5
 
0.2%
Other Punctuation 3
 
0.1%
Dash Punctuation 3
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
I 4
12.1%
C 4
12.1%
E 3
9.1%
A 3
9.1%
O 3
9.1%
V 2
 
6.1%
S 2
 
6.1%
R 2
 
6.1%
Z 2
 
6.1%
D 2
 
6.1%
Other values (6) 6
18.2%
Decimal Number
ValueCountFrequency (%)
1 2528
99.4%
0 4
 
0.2%
2 4
 
0.2%
9 2
 
0.1%
3 2
 
0.1%
5 1
 
< 0.1%
8 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
5
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2553
98.7%
Latin 33
 
1.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
I 4
12.1%
C 4
12.1%
E 3
9.1%
A 3
9.1%
O 3
9.1%
V 2
 
6.1%
S 2
 
6.1%
R 2
 
6.1%
Z 2
 
6.1%
D 2
 
6.1%
Other values (6) 6
18.2%
Common
ValueCountFrequency (%)
1 2528
99.0%
5
 
0.2%
0 4
 
0.2%
2 4
 
0.2%
/ 3
 
0.1%
- 3
 
0.1%
9 2
 
0.1%
3 2
 
0.1%
5 1
 
< 0.1%
8 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2586
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2528
97.8%
5
 
0.2%
I 4
 
0.2%
0 4
 
0.2%
2 4
 
0.2%
C 4
 
0.2%
/ 3
 
0.1%
E 3
 
0.1%
A 3
 
0.1%
O 3
 
0.1%
Other values (16) 25
 
1.0%

PCR_BOCA
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct4
Distinct (%)0.4%
Missing234768
Missing (%)99.6%
Memory size9.0 MiB
1
911 
85 - COVID-19 ASTRAZENECA/FIOCRUZ - COVISHIELD
 
1
13/03/2023
 
1
04/06/2023
 
1

Length

Max length46
Median length1
Mean length1.0689278
Min length1

Characters and Unicode

Total characters977
Distinct characters28
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 911
 
0.4%
85 - COVID-19 ASTRAZENECA/FIOCRUZ - COVISHIELD 1
 
< 0.1%
13/03/2023 1
 
< 0.1%
04/06/2023 1
 
< 0.1%
(Missing) 234768
99.6%

Length

2023-09-22T21:42:04.369208image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:04.577624image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1 911
99.1%
2
 
0.2%
85 1
 
0.1%
covid-19 1
 
0.1%
astrazeneca/fiocruz 1
 
0.1%
covishield 1
 
0.1%
13/03/2023 1
 
0.1%
04/06/2023 1
 
0.1%

Most occurring characters

ValueCountFrequency (%)
1 913
93.4%
5
 
0.5%
0 5
 
0.5%
/ 5
 
0.5%
2 4
 
0.4%
C 4
 
0.4%
I 4
 
0.4%
3 4
 
0.4%
- 3
 
0.3%
O 3
 
0.3%
Other values (18) 27
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 931
95.3%
Uppercase Letter 33
 
3.4%
Space Separator 5
 
0.5%
Other Punctuation 5
 
0.5%
Dash Punctuation 3
 
0.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 4
12.1%
I 4
12.1%
O 3
9.1%
A 3
9.1%
E 3
9.1%
Z 2
 
6.1%
R 2
 
6.1%
S 2
 
6.1%
D 2
 
6.1%
V 2
 
6.1%
Other values (6) 6
18.2%
Decimal Number
ValueCountFrequency (%)
1 913
98.1%
0 5
 
0.5%
2 4
 
0.4%
3 4
 
0.4%
8 1
 
0.1%
9 1
 
0.1%
5 1
 
0.1%
4 1
 
0.1%
6 1
 
0.1%
Space Separator
ValueCountFrequency (%)
5
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 944
96.6%
Latin 33
 
3.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
C 4
12.1%
I 4
12.1%
O 3
9.1%
A 3
9.1%
E 3
9.1%
Z 2
 
6.1%
R 2
 
6.1%
S 2
 
6.1%
D 2
 
6.1%
V 2
 
6.1%
Other values (6) 6
18.2%
Common
ValueCountFrequency (%)
1 913
96.7%
5
 
0.5%
0 5
 
0.5%
/ 5
 
0.5%
2 4
 
0.4%
3 4
 
0.4%
- 3
 
0.3%
8 1
 
0.1%
9 1
 
0.1%
5 1
 
0.1%
Other values (2) 2
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 977
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 913
93.4%
5
 
0.5%
0 5
 
0.5%
/ 5
 
0.5%
2 4
 
0.4%
C 4
 
0.4%
I 4
 
0.4%
3 4
 
0.4%
- 3
 
0.3%
O 3
 
0.3%
Other values (18) 27
 
2.8%

PCR_RINO
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct4
Distinct (%)< 0.1%
Missing225825
Missing (%)95.8%
Memory size9.2 MiB
1
9853 
2
 
2
85 - COVID-19 ASTRAZENECA/FIOCRUZ - COVISHIELD
 
1
13/03/2023
 
1

Length

Max length46
Median length1
Mean length1.0054783
Min length1

Characters and Unicode

Total characters9911
Distinct characters26
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 9853
 
4.2%
2 2
 
< 0.1%
85 - COVID-19 ASTRAZENECA/FIOCRUZ - COVISHIELD 1
 
< 0.1%
13/03/2023 1
 
< 0.1%
(Missing) 225825
95.8%

Length

2023-09-22T21:42:04.910248image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:05.264241image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1 9853
99.9%
2 2
 
< 0.1%
2
 
< 0.1%
85 1
 
< 0.1%
covid-19 1
 
< 0.1%
astrazeneca/fiocruz 1
 
< 0.1%
covishield 1
 
< 0.1%
13/03/2023 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
1 9855
99.4%
5
 
0.1%
2 4
 
< 0.1%
C 4
 
< 0.1%
I 4
 
< 0.1%
3 3
 
< 0.1%
/ 3
 
< 0.1%
- 3
 
< 0.1%
O 3
 
< 0.1%
E 3
 
< 0.1%
Other values (16) 24
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9867
99.6%
Uppercase Letter 33
 
0.3%
Space Separator 5
 
0.1%
Other Punctuation 3
 
< 0.1%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 4
12.1%
I 4
12.1%
O 3
9.1%
E 3
9.1%
A 3
9.1%
Z 2
 
6.1%
R 2
 
6.1%
S 2
 
6.1%
D 2
 
6.1%
V 2
 
6.1%
Other values (6) 6
18.2%
Decimal Number
ValueCountFrequency (%)
1 9855
99.9%
2 4
 
< 0.1%
3 3
 
< 0.1%
0 2
 
< 0.1%
9 1
 
< 0.1%
5 1
 
< 0.1%
8 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
5
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9878
99.7%
Latin 33
 
0.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
C 4
12.1%
I 4
12.1%
O 3
9.1%
E 3
9.1%
A 3
9.1%
Z 2
 
6.1%
R 2
 
6.1%
S 2
 
6.1%
D 2
 
6.1%
V 2
 
6.1%
Other values (6) 6
18.2%
Common
ValueCountFrequency (%)
1 9855
99.8%
5
 
0.1%
2 4
 
< 0.1%
3 3
 
< 0.1%
/ 3
 
< 0.1%
- 3
 
< 0.1%
0 2
 
< 0.1%
9 1
 
< 0.1%
5 1
 
< 0.1%
8 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9911
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 9855
99.4%
5
 
0.1%
2 4
 
< 0.1%
C 4
 
< 0.1%
I 4
 
< 0.1%
3 3
 
< 0.1%
/ 3
 
< 0.1%
- 3
 
< 0.1%
O 3
 
< 0.1%
E 3
 
< 0.1%
Other values (16) 24
 
0.2%

PCR_OUTRO
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct4
Distinct (%)0.2%
Missing234057
Missing (%)99.3%
Memory size9.0 MiB
1
1621 
4
 
2
85 - COVID-19 ASTRAZENECA/FIOCRUZ - COVISHIELD
 
1
0
 
1

Length

Max length46
Median length1
Mean length1.0276923
Min length1

Characters and Unicode

Total characters1670
Distinct characters25
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 1621
 
0.7%
4 2
 
< 0.1%
85 - COVID-19 ASTRAZENECA/FIOCRUZ - COVISHIELD 1
 
< 0.1%
0 1
 
< 0.1%
(Missing) 234057
99.3%

Length

2023-09-22T21:42:05.599497image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:05.956419image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1 1621
99.4%
4 2
 
0.1%
2
 
0.1%
85 1
 
0.1%
covid-19 1
 
0.1%
astrazeneca/fiocruz 1
 
0.1%
covishield 1
 
0.1%
0 1
 
0.1%

Most occurring characters

ValueCountFrequency (%)
1 1622
97.1%
5
 
0.3%
C 4
 
0.2%
I 4
 
0.2%
E 3
 
0.2%
O 3
 
0.2%
A 3
 
0.2%
- 3
 
0.2%
4 2
 
0.1%
V 2
 
0.1%
Other values (15) 19
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1628
97.5%
Uppercase Letter 33
 
2.0%
Space Separator 5
 
0.3%
Dash Punctuation 3
 
0.2%
Other Punctuation 1
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 4
12.1%
I 4
12.1%
E 3
9.1%
O 3
9.1%
A 3
9.1%
V 2
 
6.1%
R 2
 
6.1%
S 2
 
6.1%
Z 2
 
6.1%
D 2
 
6.1%
Other values (6) 6
18.2%
Decimal Number
ValueCountFrequency (%)
1 1622
99.6%
4 2
 
0.1%
9 1
 
0.1%
5 1
 
0.1%
8 1
 
0.1%
0 1
 
0.1%
Space Separator
ValueCountFrequency (%)
5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1637
98.0%
Latin 33
 
2.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
C 4
12.1%
I 4
12.1%
E 3
9.1%
O 3
9.1%
A 3
9.1%
V 2
 
6.1%
R 2
 
6.1%
S 2
 
6.1%
Z 2
 
6.1%
D 2
 
6.1%
Other values (6) 6
18.2%
Common
ValueCountFrequency (%)
1 1622
99.1%
5
 
0.3%
- 3
 
0.2%
4 2
 
0.1%
9 1
 
0.1%
5 1
 
0.1%
8 1
 
0.1%
/ 1
 
0.1%
0 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1670
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1622
97.1%
5
 
0.3%
C 4
 
0.2%
I 4
 
0.2%
E 3
 
0.2%
O 3
 
0.2%
A 3
 
0.2%
- 3
 
0.2%
4 2
 
0.1%
V 2
 
0.1%
Other values (15) 19
 
1.1%

DS_PCR_OUT
Text

MISSING 

Distinct155
Distinct (%)10.2%
Missing234160
Missing (%)99.4%
Memory size7.2 MiB
2023-09-22T21:42:06.366279image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length30
Median length11
Mean length14.118265
Min length1

Characters and Unicode

Total characters21488
Distinct characters39
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique96 ?
Unique (%)6.3%

Sample

1st rowINFLUENZA B
2nd rowENTEROVIRUS
3rd rowENTEROVIRUS
4th rowCORONAVIRUS OC43
5th rowCORONAVIRUS SAZONAL
ValueCountFrequency (%)
enterovirus 767
32.6%
coronavirus 512
21.8%
oc43 334
14.2%
sazonal 69
 
2.9%
nl63 57
 
2.4%
humano 43
 
1.8%
influenza 37
 
1.6%
b 35
 
1.5%
sub 29
 
1.2%
subtipo 27
 
1.1%
Other values (110) 442
18.8%
2023-09-22T21:42:06.996606image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
R 2912
13.6%
O 2589
12.0%
E 1844
8.6%
N 1709
8.0%
I 1689
7.9%
S 1683
7.8%
U 1642
7.6%
V 1463
 
6.8%
C 1065
 
5.0%
A 987
 
4.6%
Other values (29) 3905
18.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 19441
90.5%
Decimal Number 1029
 
4.8%
Space Separator 830
 
3.9%
Other Punctuation 57
 
0.3%
Open Punctuation 56
 
0.3%
Close Punctuation 56
 
0.3%
Dash Punctuation 16
 
0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R 2912
15.0%
O 2589
13.3%
E 1844
9.5%
N 1709
8.8%
I 1689
8.7%
S 1683
8.7%
U 1642
8.4%
V 1463
7.5%
C 1065
 
5.5%
A 987
 
5.1%
Other values (13) 1858
9.6%
Decimal Number
ValueCountFrequency (%)
3 444
43.1%
4 382
37.1%
6 65
 
6.3%
2 59
 
5.7%
9 33
 
3.2%
1 26
 
2.5%
0 20
 
1.9%
Other Punctuation
ValueCountFrequency (%)
. 35
61.4%
/ 12
 
21.1%
, 9
 
15.8%
; 1
 
1.8%
Space Separator
ValueCountFrequency (%)
830
100.0%
Open Punctuation
ValueCountFrequency (%)
( 56
100.0%
Close Punctuation
ValueCountFrequency (%)
) 56
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%
Math Symbol
ValueCountFrequency (%)
+ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 19441
90.5%
Common 2047
 
9.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
R 2912
15.0%
O 2589
13.3%
E 1844
9.5%
N 1709
8.8%
I 1689
8.7%
S 1683
8.7%
U 1642
8.4%
V 1463
7.5%
C 1065
 
5.5%
A 987
 
5.1%
Other values (13) 1858
9.6%
Common
ValueCountFrequency (%)
830
40.5%
3 444
21.7%
4 382
18.7%
6 65
 
3.2%
2 59
 
2.9%
( 56
 
2.7%
) 56
 
2.7%
. 35
 
1.7%
9 33
 
1.6%
1 26
 
1.3%
Other values (6) 61
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21488
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
R 2912
13.6%
O 2589
12.0%
E 1844
8.6%
N 1709
8.0%
I 1689
7.9%
S 1683
7.8%
U 1642
7.6%
V 1463
 
6.8%
C 1065
 
5.0%
A 987
 
4.6%
Other values (29) 3905
18.2%

CLASSI_FIN
Categorical

HIGH CORRELATION  MISSING 

Distinct8
Distinct (%)< 0.1%
Missing19928
Missing (%)8.5%
Memory size12.7 MiB
4
122224 
2
41267 
5
34996 
1
14493 
3
 
2771
Other values (3)
 
3

Length

Max length10
Median length1
Mean length1.0000695
Min length1

Characters and Unicode

Total characters215769
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row4
2nd row4
3rd row5
4th row4
5th row4

Common Values

ValueCountFrequency (%)
4 122224
51.9%
2 41267
 
17.5%
5 34996
 
14.8%
1 14493
 
6.1%
3 2771
 
1.2%
06/02/2023 1
 
< 0.1%
9 1
 
< 0.1%
ABX0529 1
 
< 0.1%
(Missing) 19928
 
8.5%

Length

2023-09-22T21:42:07.178068image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:07.379157image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
4 122224
56.6%
2 41267
 
19.1%
5 34996
 
16.2%
1 14493
 
6.7%
3 2771
 
1.3%
06/02/2023 1
 
< 0.1%
9 1
 
< 0.1%
abx0529 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
4 122224
56.6%
2 41271
 
19.1%
5 34997
 
16.2%
1 14493
 
6.7%
3 2772
 
1.3%
0 4
 
< 0.1%
/ 2
 
< 0.1%
9 2
 
< 0.1%
6 1
 
< 0.1%
A 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 215764
> 99.9%
Uppercase Letter 3
 
< 0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 122224
56.6%
2 41271
 
19.1%
5 34997
 
16.2%
1 14493
 
6.7%
3 2772
 
1.3%
0 4
 
< 0.1%
9 2
 
< 0.1%
6 1
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
A 1
33.3%
B 1
33.3%
X 1
33.3%
Other Punctuation
ValueCountFrequency (%)
/ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 215766
> 99.9%
Latin 3
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
4 122224
56.6%
2 41271
 
19.1%
5 34997
 
16.2%
1 14493
 
6.7%
3 2772
 
1.3%
0 4
 
< 0.1%
/ 2
 
< 0.1%
9 2
 
< 0.1%
6 1
 
< 0.1%
Latin
ValueCountFrequency (%)
A 1
33.3%
B 1
33.3%
X 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 215769
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 122224
56.6%
2 41271
 
19.1%
5 34997
 
16.2%
1 14493
 
6.7%
3 2772
 
1.3%
0 4
 
< 0.1%
/ 2
 
< 0.1%
9 2
 
< 0.1%
6 1
 
< 0.1%
A 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

CLASSI_OUT
Text

MISSING 

Distinct453
Distinct (%)22.5%
Missing233671
Missing (%)99.1%
Memory size7.3 MiB
2023-09-22T21:42:07.762352image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length30
Median length27
Mean length13.989557
Min length1

Characters and Unicode

Total characters28133
Distinct characters45
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique300 ?
Unique (%)14.9%

Sample

1st rowCRISE ASMATICA
2nd rowMICOBACTERIA TUBERCULOSE
3rd rowTUBERCULOSE
4th rowBRONQUITE
5th rowDISPNEIA
ValueCountFrequency (%)
pneumonia 746
22.8%
bacteriana 147
 
4.5%
virus 107
 
3.3%
sincicial 103
 
3.2%
tuberculose 102
 
3.1%
bronquiolite 102
 
3.1%
pnm 94
 
2.9%
respiratorio 87
 
2.7%
asma 87
 
2.7%
64
 
2.0%
Other values (442) 1627
49.8%
2023-09-22T21:42:08.378019image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 2892
10.3%
I 2838
10.1%
N 2825
10.0%
E 2528
 
9.0%
O 2430
 
8.6%
U 1961
 
7.0%
R 1695
 
6.0%
P 1521
 
5.4%
M 1414
 
5.0%
C 1368
 
4.9%
Other values (35) 6661
23.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 26611
94.6%
Space Separator 1261
 
4.5%
Other Punctuation 157
 
0.6%
Decimal Number 56
 
0.2%
Dash Punctuation 24
 
0.1%
Math Symbol 23
 
0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 2892
10.9%
I 2838
10.7%
N 2825
10.6%
E 2528
9.5%
O 2430
9.1%
U 1961
 
7.4%
R 1695
 
6.4%
P 1521
 
5.7%
M 1414
 
5.3%
C 1368
 
5.1%
Other values (16) 5139
19.3%
Decimal Number
ValueCountFrequency (%)
1 14
25.0%
3 8
14.3%
8 6
10.7%
5 6
10.7%
0 6
10.7%
6 5
 
8.9%
4 5
 
8.9%
2 3
 
5.4%
9 3
 
5.4%
Other Punctuation
ValueCountFrequency (%)
/ 62
39.5%
, 48
30.6%
. 39
24.8%
? 6
 
3.8%
; 2
 
1.3%
Math Symbol
ValueCountFrequency (%)
+ 22
95.7%
= 1
 
4.3%
Space Separator
ValueCountFrequency (%)
1261
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Close Punctuation
ValueCountFrequency (%)
] 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 26611
94.6%
Common 1522
 
5.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 2892
10.9%
I 2838
10.7%
N 2825
10.6%
E 2528
9.5%
O 2430
9.1%
U 1961
 
7.4%
R 1695
 
6.4%
P 1521
 
5.7%
M 1414
 
5.3%
C 1368
 
5.1%
Other values (16) 5139
19.3%
Common
ValueCountFrequency (%)
1261
82.9%
/ 62
 
4.1%
, 48
 
3.2%
. 39
 
2.6%
- 24
 
1.6%
+ 22
 
1.4%
1 14
 
0.9%
3 8
 
0.5%
? 6
 
0.4%
8 6
 
0.4%
Other values (9) 32
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28133
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 2892
10.3%
I 2838
10.1%
N 2825
10.0%
E 2528
 
9.0%
O 2430
 
8.6%
U 1961
 
7.0%
R 1695
 
6.0%
P 1521
 
5.4%
M 1414
 
5.0%
C 1368
 
4.9%
Other values (35) 6661
23.7%

CRITERIO
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct7
Distinct (%)< 0.1%
Missing28823
Missing (%)12.2%
Memory size12.5 MiB
1
191018 
2
 
9406
3
 
6276
4
 
156
23/03/2023
 
1
Other values (2)
 
2

Length

Max length10
Median length1
Mean length1.0001305
Min length1

Characters and Unicode

Total characters206886
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row2
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 191018
81.0%
2 9406
 
4.0%
3 6276
 
2.7%
4 156
 
0.1%
23/03/2023 1
 
< 0.1%
26/05/2023 1
 
< 0.1%
17/08/2023 1
 
< 0.1%
(Missing) 28823
 
12.2%

Length

2023-09-22T21:42:08.593019image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:08.783715image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1 191018
92.3%
2 9406
 
4.5%
3 6276
 
3.0%
4 156
 
0.1%
23/03/2023 1
 
< 0.1%
26/05/2023 1
 
< 0.1%
17/08/2023 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
1 191019
92.3%
2 9414
 
4.6%
3 6281
 
3.0%
4 156
 
0.1%
/ 6
 
< 0.1%
0 6
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 206880
> 99.9%
Other Punctuation 6
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 191019
92.3%
2 9414
 
4.6%
3 6281
 
3.0%
4 156
 
0.1%
0 6
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
/ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 206886
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 191019
92.3%
2 9414
 
4.6%
3 6281
 
3.0%
4 156
 
0.1%
/ 6
 
< 0.1%
0 6
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 206886
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 191019
92.3%
2 9414
 
4.6%
3 6281
 
3.0%
4 156
 
0.1%
/ 6
 
< 0.1%
0 6
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%

EVOLUCAO
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct8
Distinct (%)< 0.1%
Missing34629
Missing (%)14.7%
Memory size12.4 MiB
1
170919 
2
18491 
9
 
5959
3
 
5680
13/04/2023
 
1
Other values (3)
 
3

Length

Max length10
Median length1
Mean length1.0001791
Min length1

Characters and Unicode

Total characters201089
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 170919
72.5%
2 18491
 
7.8%
9 5959
 
2.5%
3 5680
 
2.4%
13/04/2023 1
 
< 0.1%
23/05/2023 1
 
< 0.1%
27/04/2022 1
 
< 0.1%
28/08/2023 1
 
< 0.1%
(Missing) 34629
 
14.7%

Length

2023-09-22T21:42:08.958186image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:09.156091image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1 170919
85.0%
2 18491
 
9.2%
9 5959
 
3.0%
3 5680
 
2.8%
13/04/2023 1
 
< 0.1%
23/05/2023 1
 
< 0.1%
27/04/2022 1
 
< 0.1%
28/08/2023 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
1 170920
85.0%
2 18503
 
9.2%
9 5959
 
3.0%
3 5685
 
2.8%
/ 8
 
< 0.1%
0 8
 
< 0.1%
4 2
 
< 0.1%
8 2
 
< 0.1%
5 1
 
< 0.1%
7 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 201081
> 99.9%
Other Punctuation 8
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 170920
85.0%
2 18503
 
9.2%
9 5959
 
3.0%
3 5685
 
2.8%
0 8
 
< 0.1%
4 2
 
< 0.1%
8 2
 
< 0.1%
5 1
 
< 0.1%
7 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
/ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 201089
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 170920
85.0%
2 18503
 
9.2%
9 5959
 
3.0%
3 5685
 
2.8%
/ 8
 
< 0.1%
0 8
 
< 0.1%
4 2
 
< 0.1%
8 2
 
< 0.1%
5 1
 
< 0.1%
7 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 201089
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 170920
85.0%
2 18503
 
9.2%
9 5959
 
3.0%
3 5685
 
2.8%
/ 8
 
< 0.1%
0 8
 
< 0.1%
4 2
 
< 0.1%
8 2
 
< 0.1%
5 1
 
< 0.1%
7 1
 
< 0.1%

DT_EVOLUCA
Text

MISSING 

Distinct262
Distinct (%)0.1%
Missing51543
Missing (%)21.9%
Memory size13.3 MiB
2023-09-22T21:42:09.487732image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length46
Median length10
Mean length10.000147
Min length1

Characters and Unicode

Total characters1841417
Distinct characters29
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row23/01/2023
2nd row18/01/2023
3rd row12/01/2023
4th row01/02/2023
5th row07/02/2023
ValueCountFrequency (%)
26/05/2023 1257
 
0.7%
30/05/2023 1253
 
0.7%
25/05/2023 1201
 
0.7%
10/05/2023 1166
 
0.6%
20/04/2023 1165
 
0.6%
02/06/2023 1156
 
0.6%
29/05/2023 1136
 
0.6%
28/04/2023 1129
 
0.6%
12/05/2023 1120
 
0.6%
05/05/2023 1118
 
0.6%
Other values (256) 172443
93.6%
2023-09-22T21:42:10.010079image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 464028
25.2%
0 439431
23.9%
/ 368275
20.0%
3 238644
13.0%
1 96103
 
5.2%
5 49294
 
2.7%
4 46537
 
2.5%
6 45100
 
2.4%
7 39332
 
2.1%
8 33567
 
1.8%
Other values (19) 21106
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1473101
80.0%
Other Punctuation 368275
 
20.0%
Uppercase Letter 33
 
< 0.1%
Space Separator 5
 
< 0.1%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
I 4
12.1%
C 4
12.1%
E 3
9.1%
A 3
9.1%
O 3
9.1%
D 2
 
6.1%
V 2
 
6.1%
S 2
 
6.1%
R 2
 
6.1%
Z 2
 
6.1%
Other values (6) 6
18.2%
Decimal Number
ValueCountFrequency (%)
2 464028
31.5%
0 439431
29.8%
3 238644
16.2%
1 96103
 
6.5%
5 49294
 
3.3%
4 46537
 
3.2%
6 45100
 
3.1%
7 39332
 
2.7%
8 33567
 
2.3%
9 21065
 
1.4%
Other Punctuation
ValueCountFrequency (%)
/ 368275
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1841384
> 99.9%
Latin 33
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
I 4
12.1%
C 4
12.1%
E 3
9.1%
A 3
9.1%
O 3
9.1%
D 2
 
6.1%
V 2
 
6.1%
S 2
 
6.1%
R 2
 
6.1%
Z 2
 
6.1%
Other values (6) 6
18.2%
Common
ValueCountFrequency (%)
2 464028
25.2%
0 439431
23.9%
/ 368275
20.0%
3 238644
13.0%
1 96103
 
5.2%
5 49294
 
2.7%
4 46537
 
2.5%
6 45100
 
2.4%
7 39332
 
2.1%
8 33567
 
1.8%
Other values (3) 21073
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1841417
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 464028
25.2%
0 439431
23.9%
/ 368275
20.0%
3 238644
13.0%
1 96103
 
5.2%
5 49294
 
2.7%
4 46537
 
2.5%
6 45100
 
2.4%
7 39332
 
2.1%
8 33567
 
1.8%
Other values (19) 21106
 
1.1%

DT_ENCERRA
Text

MISSING 

Distinct263
Distinct (%)0.1%
Missing35512
Missing (%)15.1%
Memory size13.9 MiB
2023-09-22T21:42:10.333535image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9998651
Min length1

Characters and Unicode

Total characters2001673
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row31/01/2023
2nd row01/02/2023
3rd row07/02/2023
4th row02/02/2023
5th row09/02/2023
ValueCountFrequency (%)
12/06/2023 1804
 
0.9%
24/04/2023 1787
 
0.9%
05/06/2023 1753
 
0.9%
30/05/2023 1739
 
0.9%
29/05/2023 1695
 
0.8%
15/05/2023 1657
 
0.8%
11/04/2023 1653
 
0.8%
25/04/2023 1635
 
0.8%
19/06/2023 1620
 
0.8%
22/05/2023 1609
 
0.8%
Other values (253) 183218
91.5%
2023-09-22T21:42:10.817638image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 499603
25.0%
0 474505
23.7%
/ 400332
20.0%
3 258271
12.9%
1 101434
 
5.1%
5 53842
 
2.7%
6 50137
 
2.5%
4 48430
 
2.4%
7 46650
 
2.3%
8 43016
 
2.1%
Other values (6) 25453
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1601336
80.0%
Other Punctuation 400332
 
20.0%
Uppercase Letter 5
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 499603
31.2%
0 474505
29.6%
3 258271
16.1%
1 101434
 
6.3%
5 53842
 
3.4%
6 50137
 
3.1%
4 48430
 
3.0%
7 46650
 
2.9%
8 43016
 
2.7%
9 25448
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
P 1
20.0%
V 1
20.0%
C 1
20.0%
D 1
20.0%
Z 1
20.0%
Other Punctuation
ValueCountFrequency (%)
/ 400332
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2001668
> 99.9%
Latin 5
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
2 499603
25.0%
0 474505
23.7%
/ 400332
20.0%
3 258271
12.9%
1 101434
 
5.1%
5 53842
 
2.7%
6 50137
 
2.5%
4 48430
 
2.4%
7 46650
 
2.3%
8 43016
 
2.1%
Latin
ValueCountFrequency (%)
P 1
20.0%
V 1
20.0%
C 1
20.0%
D 1
20.0%
Z 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2001673
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 499603
25.0%
0 474505
23.7%
/ 400332
20.0%
3 258271
12.9%
1 101434
 
5.1%
5 53842
 
2.7%
6 50137
 
2.5%
4 48430
 
2.4%
7 46650
 
2.3%
8 43016
 
2.1%
Other values (6) 25453
 
1.3%
Distinct273
Distinct (%)0.1%
Missing22
Missing (%)< 0.1%
Memory size15.1 MiB
2023-09-22T21:42:11.151301image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9998854
Min length1

Characters and Unicode

Total characters2356573
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)< 0.1%

Sample

1st row20/01/2023
2nd row23/01/2023
3rd row25/01/2023
4th row27/01/2023
5th row06/02/2023
ValueCountFrequency (%)
12/06/2023 2198
 
0.9%
11/04/2023 2152
 
0.9%
29/05/2023 2064
 
0.9%
22/05/2023 2062
 
0.9%
24/04/2023 2025
 
0.9%
30/05/2023 2024
 
0.9%
02/05/2023 1991
 
0.8%
25/04/2023 1965
 
0.8%
05/06/2023 1944
 
0.8%
09/05/2023 1943
 
0.8%
Other values (263) 215292
91.4%
2023-09-22T21:42:11.642753image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 589049
25.0%
0 558141
23.7%
/ 471314
20.0%
3 306128
13.0%
1 126123
 
5.4%
5 62932
 
2.7%
6 58933
 
2.5%
4 57534
 
2.4%
7 51014
 
2.2%
8 45390
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1885259
80.0%
Other Punctuation 471314
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 589049
31.2%
0 558141
29.6%
3 306128
16.2%
1 126123
 
6.7%
5 62932
 
3.3%
6 58933
 
3.1%
4 57534
 
3.1%
7 51014
 
2.7%
8 45390
 
2.4%
9 30015
 
1.6%
Other Punctuation
ValueCountFrequency (%)
/ 471314
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2356573
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 589049
25.0%
0 558141
23.7%
/ 471314
20.0%
3 306128
13.0%
1 126123
 
5.4%
5 62932
 
2.7%
6 58933
 
2.5%
4 57534
 
2.4%
7 51014
 
2.2%
8 45390
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2356573
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 589049
25.0%
0 558141
23.7%
/ 471314
20.0%
3 306128
13.0%
1 126123
 
5.4%
5 62932
 
2.7%
6 58933
 
2.5%
4 57534
 
2.4%
7 51014
 
2.2%
8 45390
 
1.9%

HISTO_VGM
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing23
Missing (%)< 0.1%
Memory size13.5 MiB
0.0
235657 
2.0
 
2

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters706977
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 235657
> 99.9%
2.0 2
 
< 0.1%
(Missing) 23
 
< 0.1%

Length

2023-09-22T21:42:11.842911image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:11.998751image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
0.0 235657
> 99.9%
2.0 2
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 471316
66.7%
. 235659
33.3%
2 2
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 471318
66.7%
Other Punctuation 235659
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 471316
> 99.9%
2 2
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 235659
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 706977
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 471316
66.7%
. 235659
33.3%
2 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 706977
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 471316
66.7%
. 235659
33.3%
2 2
 
< 0.1%

PAIS_VGM
Categorical

HIGH CORRELATION  MISSING  UNIFORM 

Distinct2
Distinct (%)100.0%
Missing235680
Missing (%)> 99.9%
Memory size9.0 MiB
2.0
1.0

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters6
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row2.0
2nd row1.0

Common Values

ValueCountFrequency (%)
2.0 1
 
< 0.1%
1.0 1
 
< 0.1%
(Missing) 235680
> 99.9%

Length

2023-09-22T21:42:12.129814image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:12.300329image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
2.0 1
50.0%
1.0 1
50.0%

Most occurring characters

ValueCountFrequency (%)
. 2
33.3%
0 2
33.3%
2 1
16.7%
1 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4
66.7%
Other Punctuation 2
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2
50.0%
2 1
25.0%
1 1
25.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 2
33.3%
0 2
33.3%
2 1
16.7%
1 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 2
33.3%
0 2
33.3%
2 1
16.7%
1 1
16.7%

CO_PS_VGM
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing235681
Missing (%)> 99.9%
Memory size1.8 MiB
Minimum2021-04-08 00:00:00
Maximum2021-04-08 00:00:00
2023-09-22T21:42:12.428468image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-22T21:42:12.555517image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

LO_PS_VGM
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing235681
Missing (%)> 99.9%
Memory size1.8 MiB
Minimum2021-10-19 00:00:00
Maximum2021-10-19 00:00:00
2023-09-22T21:42:12.694780image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-22T21:42:12.822815image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

DT_VGM
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing235681
Missing (%)> 99.9%
Memory size1.8 MiB
Minimum2022-03-18 00:00:00
Maximum2022-03-18 00:00:00
2023-09-22T21:42:12.954324image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-22T21:42:13.097131image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

DT_RT_VGM
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing235679
Missing (%)> 99.9%
Memory size7.2 MiB
2023-09-22T21:42:13.253743image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length32
Median length1
Mean length11.333333
Min length1

Characters and Unicode

Total characters34
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row2
2nd row87 - COVID-19 PFIZER - COMIRNATY
3rd row6
ValueCountFrequency (%)
2
25.0%
2 1
12.5%
87 1
12.5%
covid-19 1
12.5%
pfizer 1
12.5%
comirnaty 1
12.5%
6 1
12.5%
2023-09-22T21:42:13.600438image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5
 
14.7%
- 3
 
8.8%
I 3
 
8.8%
C 2
 
5.9%
O 2
 
5.9%
R 2
 
5.9%
2 1
 
2.9%
Z 1
 
2.9%
Y 1
 
2.9%
T 1
 
2.9%
Other values (13) 13
38.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 20
58.8%
Decimal Number 6
 
17.6%
Space Separator 5
 
14.7%
Dash Punctuation 3
 
8.8%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
I 3
15.0%
C 2
 
10.0%
O 2
 
10.0%
R 2
 
10.0%
Z 1
 
5.0%
Y 1
 
5.0%
T 1
 
5.0%
A 1
 
5.0%
N 1
 
5.0%
M 1
 
5.0%
Other values (5) 5
25.0%
Decimal Number
ValueCountFrequency (%)
2 1
16.7%
9 1
16.7%
8 1
16.7%
1 1
16.7%
7 1
16.7%
6 1
16.7%
Space Separator
ValueCountFrequency (%)
5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 20
58.8%
Common 14
41.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
I 3
15.0%
C 2
 
10.0%
O 2
 
10.0%
R 2
 
10.0%
Z 1
 
5.0%
Y 1
 
5.0%
T 1
 
5.0%
A 1
 
5.0%
N 1
 
5.0%
M 1
 
5.0%
Other values (5) 5
25.0%
Common
ValueCountFrequency (%)
5
35.7%
- 3
21.4%
2 1
 
7.1%
9 1
 
7.1%
8 1
 
7.1%
1 1
 
7.1%
7 1
 
7.1%
6 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 34
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5
 
14.7%
- 3
 
8.8%
I 3
 
8.8%
C 2
 
5.9%
O 2
 
5.9%
R 2
 
5.9%
2 1
 
2.9%
Z 1
 
2.9%
Y 1
 
2.9%
T 1
 
2.9%
Other values (13) 13
38.2%

PCR_SARS2
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct3
Distinct (%)< 0.1%
Missing220464
Missing (%)93.5%
Memory size9.3 MiB
1
15216 
14/05/2023
 
1
87 - COVID-19 PFIZER - COMIRNATY
 
1

Length

Max length32
Median length1
Mean length1.0026285
Min length1

Characters and Unicode

Total characters15258
Distinct characters27
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 15216
 
6.5%
14/05/2023 1
 
< 0.1%
87 - COVID-19 PFIZER - COMIRNATY 1
 
< 0.1%
(Missing) 220464
93.5%

Length

2023-09-22T21:42:13.803459image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:13.990166image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1 15216
> 99.9%
2
 
< 0.1%
14/05/2023 1
 
< 0.1%
87 1
 
< 0.1%
covid-19 1
 
< 0.1%
pfizer 1
 
< 0.1%
comirnaty 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
1 15218
99.7%
5
 
< 0.1%
I 3
 
< 0.1%
- 3
 
< 0.1%
C 2
 
< 0.1%
/ 2
 
< 0.1%
0 2
 
< 0.1%
2 2
 
< 0.1%
R 2
 
< 0.1%
O 2
 
< 0.1%
Other values (17) 17
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15228
99.8%
Uppercase Letter 20
 
0.1%
Space Separator 5
 
< 0.1%
Dash Punctuation 3
 
< 0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
I 3
15.0%
C 2
 
10.0%
R 2
 
10.0%
O 2
 
10.0%
E 1
 
5.0%
M 1
 
5.0%
F 1
 
5.0%
N 1
 
5.0%
A 1
 
5.0%
T 1
 
5.0%
Other values (5) 5
25.0%
Decimal Number
ValueCountFrequency (%)
1 15218
99.9%
0 2
 
< 0.1%
2 2
 
< 0.1%
9 1
 
< 0.1%
4 1
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%
3 1
 
< 0.1%
5 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15238
99.9%
Latin 20
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
I 3
15.0%
C 2
 
10.0%
R 2
 
10.0%
O 2
 
10.0%
E 1
 
5.0%
M 1
 
5.0%
F 1
 
5.0%
N 1
 
5.0%
A 1
 
5.0%
T 1
 
5.0%
Other values (5) 5
25.0%
Common
ValueCountFrequency (%)
1 15218
99.9%
5
 
< 0.1%
- 3
 
< 0.1%
/ 2
 
< 0.1%
0 2
 
< 0.1%
2 2
 
< 0.1%
9 1
 
< 0.1%
4 1
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15258
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15218
99.7%
5
 
< 0.1%
I 3
 
< 0.1%
- 3
 
< 0.1%
C 2
 
< 0.1%
/ 2
 
< 0.1%
0 2
 
< 0.1%
2 2
 
< 0.1%
R 2
 
< 0.1%
O 2
 
< 0.1%
Other values (17) 17
 
0.1%

PAC_COCBO
Text

MISSING 

Distinct303
Distinct (%)14.8%
Missing233631
Missing (%)99.1%
Memory size7.3 MiB
2023-09-22T21:42:14.296521image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length35
Median length6
Mean length5.4578255
Min length1

Characters and Unicode

Total characters11194
Distinct characters24
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique125 ?
Unique (%)6.1%

Sample

1st row715210
2nd row214205
3rd row354705
4th row521110
5th row622020
ValueCountFrequency (%)
xxx 377
 
18.3%
622020 166
 
8.1%
621005 123
 
6.0%
848505 94
 
4.6%
715210 63
 
3.1%
622005 43
 
2.1%
512105 43
 
2.1%
512120 42
 
2.0%
322205 35
 
1.7%
141410 35
 
1.7%
Other values (297) 1035
50.3%
2023-09-22T21:42:14.832631image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1990
17.8%
2 1987
17.8%
1 1853
16.6%
5 1729
15.4%
X 1131
10.1%
6 585
 
5.2%
3 564
 
5.0%
4 557
 
5.0%
7 402
 
3.6%
8 321
 
2.9%
Other values (14) 75
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10035
89.6%
Uppercase Letter 1149
 
10.3%
Space Separator 5
 
< 0.1%
Dash Punctuation 3
 
< 0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
X 1131
98.4%
S 3
 
0.3%
O 2
 
0.2%
V 2
 
0.2%
D 2
 
0.2%
A 2
 
0.2%
N 2
 
0.2%
C 2
 
0.2%
I 1
 
0.1%
J 1
 
0.1%
Decimal Number
ValueCountFrequency (%)
0 1990
19.8%
2 1987
19.8%
1 1853
18.5%
5 1729
17.2%
6 585
 
5.8%
3 564
 
5.6%
4 557
 
5.6%
7 402
 
4.0%
8 321
 
3.2%
9 47
 
0.5%
Space Separator
ValueCountFrequency (%)
5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10045
89.7%
Latin 1149
 
10.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1990
19.8%
2 1987
19.8%
1 1853
18.4%
5 1729
17.2%
6 585
 
5.8%
3 564
 
5.6%
4 557
 
5.5%
7 402
 
4.0%
8 321
 
3.2%
9 47
 
0.5%
Other values (3) 10
 
0.1%
Latin
ValueCountFrequency (%)
X 1131
98.4%
S 3
 
0.3%
O 2
 
0.2%
V 2
 
0.2%
D 2
 
0.2%
A 2
 
0.2%
N 2
 
0.2%
C 2
 
0.2%
I 1
 
0.1%
J 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11194
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1990
17.8%
2 1987
17.8%
1 1853
16.6%
5 1729
15.4%
X 1131
10.1%
6 585
 
5.2%
3 564
 
5.0%
4 557
 
5.0%
7 402
 
3.6%
8 321
 
2.9%
Other values (14) 75
 
0.7%

PAC_DSCBO
Text

MISSING 

Distinct305
Distinct (%)14.9%
Missing233629
Missing (%)99.1%
Memory size7.3 MiB
2023-09-22T21:42:15.176320image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length104
Median length71
Mean length23.330248
Min length1

Characters and Unicode

Total characters47897
Distinct characters36
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique127 ?
Unique (%)6.2%

Sample

1st rowPEDREIRO
2nd rowENGENHEIRO CIVIL
3rd rowREPRESENTANTE COMERCIAL AUTONOMO
4th rowVENDEDOR DE COMERCIO VAREJISTA
5th rowTRABALHADOR VOLANTE DA AGRICULTURA
ValueCountFrequency (%)
de 588
 
9.5%
nao 378
 
6.1%
informado 377
 
6.1%
trabalhador 308
 
5.0%
da 219
 
3.5%
agricultura 209
 
3.4%
geral 174
 
2.8%
volante 166
 
2.7%
em 166
 
2.7%
agropecuario 136
 
2.2%
Other values (486) 3481
56.1%
2023-09-22T21:42:15.765275image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 6123
12.8%
O 5023
10.5%
R 4532
9.5%
E 4490
9.4%
4288
 
9.0%
I 3374
 
7.0%
D 2727
 
5.7%
N 2393
 
5.0%
T 2298
 
4.8%
C 1912
 
4.0%
Other values (26) 10737
22.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 43241
90.3%
Space Separator 4288
 
9.0%
Open Punctuation 150
 
0.3%
Close Punctuation 150
 
0.3%
Other Punctuation 31
 
0.1%
Dash Punctuation 29
 
0.1%
Decimal Number 8
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 6123
14.2%
O 5023
11.6%
R 4532
10.5%
E 4490
10.4%
I 3374
 
7.8%
D 2727
 
6.3%
N 2393
 
5.5%
T 2298
 
5.3%
C 1912
 
4.4%
S 1772
 
4.1%
Other values (15) 8597
19.9%
Decimal Number
ValueCountFrequency (%)
2 2
25.0%
1 2
25.0%
9 2
25.0%
8 1
12.5%
7 1
12.5%
Other Punctuation
ValueCountFrequency (%)
, 30
96.8%
/ 1
 
3.2%
Space Separator
ValueCountFrequency (%)
4288
100.0%
Open Punctuation
ValueCountFrequency (%)
( 150
100.0%
Close Punctuation
ValueCountFrequency (%)
) 150
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 43241
90.3%
Common 4656
 
9.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 6123
14.2%
O 5023
11.6%
R 4532
10.5%
E 4490
10.4%
I 3374
 
7.8%
D 2727
 
6.3%
N 2393
 
5.5%
T 2298
 
5.3%
C 1912
 
4.4%
S 1772
 
4.1%
Other values (15) 8597
19.9%
Common
ValueCountFrequency (%)
4288
92.1%
( 150
 
3.2%
) 150
 
3.2%
, 30
 
0.6%
- 29
 
0.6%
2 2
 
< 0.1%
1 2
 
< 0.1%
9 2
 
< 0.1%
/ 1
 
< 0.1%
8 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47897
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 6123
12.8%
O 5023
10.5%
R 4532
9.5%
E 4490
9.4%
4288
 
9.0%
I 3374
 
7.0%
D 2727
 
5.7%
N 2393
 
5.0%
T 2298
 
4.8%
C 1912
 
4.0%
Other values (26) 10737
22.4%

OUT_ANIM
Text

MISSING 

Distinct109
Distinct (%)14.3%
Missing234919
Missing (%)99.7%
Memory size7.2 MiB
2023-09-22T21:42:16.032270image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length31
Median length30
Mean length8.6841415
Min length1

Characters and Unicode

Total characters6626
Distinct characters35
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)8.3%

Sample

1st rowGATO E CACHORRO
2nd rowCACHORRO
3rd rowCACHORRO
4th rowGATO
5th rowCAO
ValueCountFrequency (%)
cachorro 456
45.0%
gato 190
18.8%
e 68
 
6.7%
cao 39
 
3.8%
gatos 33
 
3.3%
gato,cachorro 14
 
1.4%
cachorros 11
 
1.1%
de 11
 
1.1%
animais 10
 
1.0%
estimacao 9
 
0.9%
Other values (83) 172
 
17.0%
2023-09-22T21:42:16.497226image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
O 1421
21.4%
C 1084
16.4%
R 1025
15.5%
A 968
14.6%
H 515
 
7.8%
T 287
 
4.3%
G 285
 
4.3%
251
 
3.8%
E 155
 
2.3%
S 126
 
1.9%
Other values (25) 509
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 6259
94.5%
Space Separator 251
 
3.8%
Other Punctuation 97
 
1.5%
Decimal Number 17
 
0.3%
Dash Punctuation 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
O 1421
22.7%
C 1084
17.3%
R 1025
16.4%
A 968
15.5%
H 515
 
8.2%
T 287
 
4.6%
G 285
 
4.6%
E 155
 
2.5%
S 126
 
2.0%
I 103
 
1.6%
Other values (13) 290
 
4.6%
Decimal Number
ValueCountFrequency (%)
2 7
41.2%
1 3
17.6%
3 3
17.6%
0 3
17.6%
7 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 64
66.0%
/ 18
 
18.6%
. 13
 
13.4%
; 2
 
2.1%
Space Separator
ValueCountFrequency (%)
251
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6259
94.5%
Common 367
 
5.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
O 1421
22.7%
C 1084
17.3%
R 1025
16.4%
A 968
15.5%
H 515
 
8.2%
T 287
 
4.6%
G 285
 
4.6%
E 155
 
2.5%
S 126
 
2.0%
I 103
 
1.6%
Other values (13) 290
 
4.6%
Common
ValueCountFrequency (%)
251
68.4%
, 64
 
17.4%
/ 18
 
4.9%
. 13
 
3.5%
2 7
 
1.9%
1 3
 
0.8%
3 3
 
0.8%
0 3
 
0.8%
; 2
 
0.5%
- 1
 
0.3%
Other values (2) 2
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6626
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
O 1421
21.4%
C 1084
16.4%
R 1025
15.5%
A 968
14.6%
H 515
 
7.8%
T 287
 
4.3%
G 285
 
4.3%
251
 
3.8%
E 155
 
2.3%
S 126
 
1.9%
Other values (25) 509
 
7.7%

DOR_ABD
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct4
Distinct (%)< 0.1%
Missing69757
Missing (%)29.6%
Memory size11.8 MiB
2
148559 
1
 
12907
9
 
4458
31045BD
 
1

Length

Max length7
Median length1
Mean length1.0000362
Min length1

Characters and Unicode

Total characters165931
Distinct characters9
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row2
2nd row9
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 148559
63.0%
1 12907
 
5.5%
9 4458
 
1.9%
31045BD 1
 
< 0.1%
(Missing) 69757
29.6%

Length

2023-09-22T21:42:16.720691image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:17.065653image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
2 148559
89.5%
1 12907
 
7.8%
9 4458
 
2.7%
31045bd 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
2 148559
89.5%
1 12908
 
7.8%
9 4458
 
2.7%
3 1
 
< 0.1%
0 1
 
< 0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
B 1
 
< 0.1%
D 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 165929
> 99.9%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 148559
89.5%
1 12908
 
7.8%
9 4458
 
2.7%
3 1
 
< 0.1%
0 1
 
< 0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
B 1
50.0%
D 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 165929
> 99.9%
Latin 2
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
2 148559
89.5%
1 12908
 
7.8%
9 4458
 
2.7%
3 1
 
< 0.1%
0 1
 
< 0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
Latin
ValueCountFrequency (%)
B 1
50.0%
D 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 165931
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 148559
89.5%
1 12908
 
7.8%
9 4458
 
2.7%
3 1
 
< 0.1%
0 1
 
< 0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
B 1
 
< 0.1%
D 1
 
< 0.1%

FADIGA
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct4
Distinct (%)< 0.1%
Missing65447
Missing (%)27.8%
Memory size11.9 MiB
2
130298 
1
36322 
9
 
3614
205F21A
 
1

Length

Max length7
Median length1
Mean length1.0000352
Min length1

Characters and Unicode

Total characters170241
Distinct characters7
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row9
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 130298
55.3%
1 36322
 
15.4%
9 3614
 
1.5%
205F21A 1
 
< 0.1%
(Missing) 65447
27.8%

Length

2023-09-22T21:42:17.412499image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:17.794364image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
2 130298
76.5%
1 36322
 
21.3%
9 3614
 
2.1%
205f21a 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
2 130300
76.5%
1 36323
 
21.3%
9 3614
 
2.1%
0 1
 
< 0.1%
5 1
 
< 0.1%
F 1
 
< 0.1%
A 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 170239
> 99.9%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 130300
76.5%
1 36323
 
21.3%
9 3614
 
2.1%
0 1
 
< 0.1%
5 1
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
F 1
50.0%
A 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 170239
> 99.9%
Latin 2
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
2 130300
76.5%
1 36323
 
21.3%
9 3614
 
2.1%
0 1
 
< 0.1%
5 1
 
< 0.1%
Latin
ValueCountFrequency (%)
F 1
50.0%
A 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 170241
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 130300
76.5%
1 36323
 
21.3%
9 3614
 
2.1%
0 1
 
< 0.1%
5 1
 
< 0.1%
F 1
 
< 0.1%
A 1
 
< 0.1%

PERD_OLFT
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct4
Distinct (%)< 0.1%
Missing71752
Missing (%)30.4%
Memory size12.1 MiB
2.0
154281 
9.0
 
7009
1.0
 
2639
3.0
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters491790
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row2.0
2nd row9.0
3rd row2.0
4th row2.0
5th row2.0

Common Values

ValueCountFrequency (%)
2.0 154281
65.5%
9.0 7009
 
3.0%
1.0 2639
 
1.1%
3.0 1
 
< 0.1%
(Missing) 71752
30.4%

Length

2023-09-22T21:42:18.158946image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:18.575233image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
2.0 154281
94.1%
9.0 7009
 
4.3%
1.0 2639
 
1.6%
3.0 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
. 163930
33.3%
0 163930
33.3%
2 154281
31.4%
9 7009
 
1.4%
1 2639
 
0.5%
3 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 327860
66.7%
Other Punctuation 163930
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 163930
50.0%
2 154281
47.1%
9 7009
 
2.1%
1 2639
 
0.8%
3 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 163930
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 491790
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 163930
33.3%
0 163930
33.3%
2 154281
31.4%
9 7009
 
1.4%
1 2639
 
0.5%
3 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 491790
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 163930
33.3%
0 163930
33.3%
2 154281
31.4%
9 7009
 
1.4%
1 2639
 
0.5%
3 1
 
< 0.1%

PERD_PALA
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct3
Distinct (%)< 0.1%
Missing72013
Missing (%)30.6%
Memory size12.1 MiB
2.0
154223 
9.0
 
6990
1.0
 
2456

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters491007
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2.0
2nd row9.0
3rd row2.0
4th row2.0
5th row2.0

Common Values

ValueCountFrequency (%)
2.0 154223
65.4%
9.0 6990
 
3.0%
1.0 2456
 
1.0%
(Missing) 72013
30.6%

Length

2023-09-22T21:42:18.968751image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:19.157984image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
2.0 154223
94.2%
9.0 6990
 
4.3%
1.0 2456
 
1.5%

Most occurring characters

ValueCountFrequency (%)
. 163669
33.3%
0 163669
33.3%
2 154223
31.4%
9 6990
 
1.4%
1 2456
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 327338
66.7%
Other Punctuation 163669
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 163669
50.0%
2 154223
47.1%
9 6990
 
2.1%
1 2456
 
0.8%
Other Punctuation
ValueCountFrequency (%)
. 163669
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 491007
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 163669
33.3%
0 163669
33.3%
2 154223
31.4%
9 6990
 
1.4%
1 2456
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 491007
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 163669
33.3%
0 163669
33.3%
2 154223
31.4%
9 6990
 
1.4%
1 2456
 
0.5%

TOMO_RES
Categorical

HIGH CORRELATION  MISSING 

Distinct8
Distinct (%)< 0.1%
Missing97974
Missing (%)41.6%
Memory size11.4 MiB
6
98388 
9
13112 
5
 
9030
1
 
7094
2
 
5260
Other values (3)
 
4824

Length

Max length10
Median length1
Mean length1.0000654
Min length1

Characters and Unicode

Total characters137717
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row6
2nd row5
3rd row1
4th row1
5th row5

Common Values

ValueCountFrequency (%)
6 98388
41.7%
9 13112
 
5.6%
5 9030
 
3.8%
1 7094
 
3.0%
2 5260
 
2.2%
3 3975
 
1.7%
4 848
 
0.4%
19/03/2023 1
 
< 0.1%
(Missing) 97974
41.6%

Length

2023-09-22T21:42:19.304239image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:19.498189image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
6 98388
71.4%
9 13112
 
9.5%
5 9030
 
6.6%
1 7094
 
5.2%
2 5260
 
3.8%
3 3975
 
2.9%
4 848
 
0.6%
19/03/2023 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
6 98388
71.4%
9 13113
 
9.5%
5 9030
 
6.6%
1 7095
 
5.2%
2 5262
 
3.8%
3 3977
 
2.9%
4 848
 
0.6%
/ 2
 
< 0.1%
0 2
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 137715
> 99.9%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 98388
71.4%
9 13113
 
9.5%
5 9030
 
6.6%
1 7095
 
5.2%
2 5262
 
3.8%
3 3977
 
2.9%
4 848
 
0.6%
0 2
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
/ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 137717
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 98388
71.4%
9 13113
 
9.5%
5 9030
 
6.6%
1 7095
 
5.2%
2 5262
 
3.8%
3 3977
 
2.9%
4 848
 
0.6%
/ 2
 
< 0.1%
0 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 137717
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 98388
71.4%
9 13113
 
9.5%
5 9030
 
6.6%
1 7095
 
5.2%
2 5262
 
3.8%
3 3977
 
2.9%
4 848
 
0.6%
/ 2
 
< 0.1%
0 2
 
< 0.1%

TOMO_OUT
Text

MISSING 

Distinct2872
Distinct (%)38.7%
Missing228258
Missing (%)96.8%
Memory size7.5 MiB
2023-09-22T21:42:19.840980image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length60
Median length30
Mean length19.198545
Min length1

Characters and Unicode

Total characters142530
Distinct characters55
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2132 ?
Unique (%)28.7%

Sample

1st rowSEM LAUDO
2nd rowDERRAME PLEURAL+ ATELECTASIA
3rd rowOPACIDADES CONTROLOBULARES
4th rowINFILTRADO PULMONAR INTERSTICI
5th rowVIDRO FOSCO
ValueCountFrequency (%)
derrame 1023
 
5.6%
pleural 960
 
5.3%
vidro 879
 
4.8%
fosco 839
 
4.6%
consolidacao 630
 
3.5%
em 510
 
2.8%
opacidades 470
 
2.6%
laudo 438
 
2.4%
de 432
 
2.4%
opacidade 373
 
2.0%
Other values (1902) 11677
64.1%
2023-09-22T21:42:20.420100image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 17708
12.4%
O 15293
10.7%
E 13010
 
9.1%
10820
 
7.6%
R 9458
 
6.6%
I 9384
 
6.6%
D 8156
 
5.7%
S 7847
 
5.5%
C 7539
 
5.3%
L 7365
 
5.2%
Other values (45) 35950
25.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 130045
91.2%
Space Separator 10851
 
7.6%
Other Punctuation 1182
 
0.8%
Decimal Number 185
 
0.1%
Math Symbol 183
 
0.1%
Dash Punctuation 47
 
< 0.1%
Open Punctuation 20
 
< 0.1%
Close Punctuation 12
 
< 0.1%
Control 5
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 17708
13.6%
O 15293
11.8%
E 13010
10.0%
R 9458
 
7.3%
I 9384
 
7.2%
D 8156
 
6.3%
S 7847
 
6.0%
C 7539
 
5.8%
L 7365
 
5.7%
N 6895
 
5.3%
Other values (15) 27390
21.1%
Other Punctuation
ValueCountFrequency (%)
, 358
30.3%
. 331
28.0%
" 208
17.6%
/ 205
17.3%
% 31
 
2.6%
; 17
 
1.4%
? 15
 
1.3%
: 15
 
1.3%
' 1
 
0.1%
¿ 1
 
0.1%
Decimal Number
ValueCountFrequency (%)
0 47
25.4%
5 30
16.2%
2 24
13.0%
1 20
10.8%
8 15
 
8.1%
9 14
 
7.6%
7 11
 
5.9%
4 9
 
4.9%
6 8
 
4.3%
3 7
 
3.8%
Math Symbol
ValueCountFrequency (%)
+ 178
97.3%
> 4
 
2.2%
< 1
 
0.5%
Space Separator
ValueCountFrequency (%)
10820
99.7%
  31
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 19
95.0%
[ 1
 
5.0%
Dash Punctuation
ValueCountFrequency (%)
- 47
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Control
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 130045
91.2%
Common 12485
 
8.8%

Most frequent character per script

Common
ValueCountFrequency (%)
10820
86.7%
, 358
 
2.9%
. 331
 
2.7%
" 208
 
1.7%
/ 205
 
1.6%
+ 178
 
1.4%
0 47
 
0.4%
- 47
 
0.4%
% 31
 
0.2%
  31
 
0.2%
Other values (20) 229
 
1.8%
Latin
ValueCountFrequency (%)
A 17708
13.6%
O 15293
11.8%
E 13010
10.0%
R 9458
 
7.3%
I 9384
 
7.2%
D 8156
 
6.3%
S 7847
 
6.0%
C 7539
 
5.8%
L 7365
 
5.7%
N 6895
 
5.3%
Other values (15) 27390
21.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 142498
> 99.9%
None 32
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 17708
12.4%
O 15293
10.7%
E 13010
 
9.1%
10820
 
7.6%
R 9458
 
6.6%
I 9384
 
6.6%
D 8156
 
5.7%
S 7847
 
5.5%
C 7539
 
5.3%
L 7365
 
5.2%
Other values (43) 35918
25.2%
None
ValueCountFrequency (%)
  31
96.9%
¿ 1
 
3.1%

DT_TOMO
Text

MISSING 

Distinct315
Distinct (%)1.3%
Missing212024
Missing (%)90.0%
Memory size8.0 MiB
2023-09-22T21:42:20.764918image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9988587
Min length1

Characters and Unicode

Total characters236553
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)0.2%

Sample

1st row04/01/2023
2nd row08/01/2023
3rd row22/01/2023
4th row31/01/2023
5th row08/01/2023
ValueCountFrequency (%)
30/05/2023 144
 
0.6%
16/05/2023 143
 
0.6%
22/05/2023 142
 
0.6%
15/05/2023 141
 
0.6%
08/05/2023 139
 
0.6%
17/04/2023 138
 
0.6%
05/06/2023 137
 
0.6%
09/03/2023 136
 
0.6%
09/05/2023 136
 
0.6%
06/03/2023 136
 
0.6%
Other values (305) 22266
94.1%
2023-09-22T21:42:21.267009image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 59711
25.2%
0 56818
24.0%
/ 47310
20.0%
3 30651
13.0%
1 13350
 
5.6%
5 5990
 
2.5%
4 5535
 
2.3%
6 5432
 
2.3%
7 4722
 
2.0%
8 4141
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 189243
80.0%
Other Punctuation 47310
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 59711
31.6%
0 56818
30.0%
3 30651
16.2%
1 13350
 
7.1%
5 5990
 
3.2%
4 5535
 
2.9%
6 5432
 
2.9%
7 4722
 
2.5%
8 4141
 
2.2%
9 2893
 
1.5%
Other Punctuation
ValueCountFrequency (%)
/ 47310
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 236553
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 59711
25.2%
0 56818
24.0%
/ 47310
20.0%
3 30651
13.0%
1 13350
 
5.6%
5 5990
 
2.5%
4 5535
 
2.3%
6 5432
 
2.3%
7 4722
 
2.0%
8 4141
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 236553
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 59711
25.2%
0 56818
24.0%
/ 47310
20.0%
3 30651
13.0%
1 13350
 
5.6%
5 5990
 
2.5%
4 5535
 
2.3%
6 5432
 
2.3%
7 4722
 
2.0%
8 4141
 
1.8%

TP_TES_AN
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct3
Distinct (%)< 0.1%
Missing136865
Missing (%)58.1%
Memory size10.7 MiB
2
94544 
1
 
4272
09/09/2021
 
1

Length

Max length10
Median length1
Mean length1.0000911
Min length1

Characters and Unicode

Total characters98826
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 94544
40.1%
1 4272
 
1.8%
09/09/2021 1
 
< 0.1%
(Missing) 136865
58.1%

Length

2023-09-22T21:42:21.475533image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:21.639817image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
2 94544
95.7%
1 4272
 
4.3%
09/09/2021 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
2 94546
95.7%
1 4273
 
4.3%
0 3
 
< 0.1%
9 2
 
< 0.1%
/ 2
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 98824
> 99.9%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 94546
95.7%
1 4273
 
4.3%
0 3
 
< 0.1%
9 2
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
/ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 98826
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 94546
95.7%
1 4273
 
4.3%
0 3
 
< 0.1%
9 2
 
< 0.1%
/ 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 98826
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 94546
95.7%
1 4273
 
4.3%
0 3
 
< 0.1%
9 2
 
< 0.1%
/ 2
 
< 0.1%

DT_RES_AN
Text

MISSING 

Distinct268
Distinct (%)0.3%
Missing135776
Missing (%)57.6%
Memory size10.5 MiB
2023-09-22T21:42:21.927227image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9999099
Min length1

Characters and Unicode

Total characters999051
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)< 0.1%

Sample

1st row03/01/2023
2nd row07/01/2023
3rd row05/02/2023
4th row04/02/2023
5th row11/02/2023
ValueCountFrequency (%)
24/04/2023 654
 
0.7%
22/05/2023 632
 
0.6%
20/03/2023 629
 
0.6%
10/04/2023 629
 
0.6%
23/05/2023 617
 
0.6%
27/03/2023 617
 
0.6%
23/03/2023 616
 
0.6%
17/04/2023 611
 
0.6%
15/05/2023 610
 
0.6%
28/03/2023 608
 
0.6%
Other values (258) 93683
93.8%
2023-09-22T21:42:22.418978image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 252624
25.3%
0 239260
23.9%
/ 199810
20.0%
3 130629
13.1%
1 55212
 
5.5%
5 25570
 
2.6%
4 24830
 
2.5%
6 22588
 
2.3%
7 19669
 
2.0%
8 17286
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 799241
80.0%
Other Punctuation 199810
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 252624
31.6%
0 239260
29.9%
3 130629
16.3%
1 55212
 
6.9%
5 25570
 
3.2%
4 24830
 
3.1%
6 22588
 
2.8%
7 19669
 
2.5%
8 17286
 
2.2%
9 11573
 
1.4%
Other Punctuation
ValueCountFrequency (%)
/ 199810
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 999051
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 252624
25.3%
0 239260
23.9%
/ 199810
20.0%
3 130629
13.1%
1 55212
 
5.5%
5 25570
 
2.6%
4 24830
 
2.5%
6 22588
 
2.3%
7 19669
 
2.0%
8 17286
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 999051
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 252624
25.3%
0 239260
23.9%
/ 199810
20.0%
3 130629
13.1%
1 55212
 
5.5%
5 25570
 
2.6%
4 24830
 
2.5%
6 22588
 
2.3%
7 19669
 
2.0%
8 17286
 
1.7%

RES_AN
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct6
Distinct (%)< 0.1%
Missing25757
Missing (%)10.9%
Infinite0
Infinite (%)0.0%
Mean3.3053614
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 MiB
2023-09-22T21:42:22.605974image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q35
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.5824194
Coefficient of variation (CV)0.47874322
Kurtosis-1.2660919
Mean3.3053614
Median Absolute Deviation (MAD)1
Skewness-0.032413259
Sum693878
Variance2.5040511
MonotonicityNot monotonic
2023-09-22T21:42:22.749965image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
5 75214
31.9%
2 67381
28.6%
4 36962
15.7%
1 29717
 
12.6%
9 588
 
0.2%
3 63
 
< 0.1%
(Missing) 25757
 
10.9%
ValueCountFrequency (%)
1 29717
 
12.6%
2 67381
28.6%
3 63
 
< 0.1%
4 36962
15.7%
5 75214
31.9%
9 588
 
0.2%
ValueCountFrequency (%)
9 588
 
0.2%
5 75214
31.9%
4 36962
15.7%
3 63
 
< 0.1%
2 67381
28.6%
1 29717
 
12.6%

POS_AN_FLU
Categorical

HIGH CORRELATION  MISSING 

Distinct4
Distinct (%)< 0.1%
Missing213225
Missing (%)90.5%
Memory size9.4 MiB
2
16300 
1
4776 
9
 
1380
86 - COVID-19 SINOVAC/BUTANTAN - CORONAVAC
 
1

Length

Max length42
Median length1
Mean length1.0018257
Min length1

Characters and Unicode

Total characters22498
Distinct characters20
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 16300
 
6.9%
1 4776
 
2.0%
9 1380
 
0.6%
86 - COVID-19 SINOVAC/BUTANTAN - CORONAVAC 1
 
< 0.1%
(Missing) 213225
90.5%

Length

2023-09-22T21:42:22.939293image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:23.124237image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
2 16300
72.6%
1 4776
 
21.3%
9 1380
 
6.1%
2
 
< 0.1%
86 1
 
< 0.1%
covid-19 1
 
< 0.1%
sinovac/butantan 1
 
< 0.1%
coronavac 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
2 16300
72.5%
1 4777
 
21.2%
9 1381
 
6.1%
A 5
 
< 0.1%
5
 
< 0.1%
N 4
 
< 0.1%
C 4
 
< 0.1%
O 4
 
< 0.1%
- 3
 
< 0.1%
V 3
 
< 0.1%
Other values (10) 12
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 22460
99.8%
Uppercase Letter 29
 
0.1%
Space Separator 5
 
< 0.1%
Dash Punctuation 3
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 5
17.2%
N 4
13.8%
C 4
13.8%
O 4
13.8%
V 3
10.3%
T 2
 
6.9%
I 2
 
6.9%
S 1
 
3.4%
D 1
 
3.4%
B 1
 
3.4%
Other values (2) 2
 
6.9%
Decimal Number
ValueCountFrequency (%)
2 16300
72.6%
1 4777
 
21.3%
9 1381
 
6.1%
6 1
 
< 0.1%
8 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22469
99.9%
Latin 29
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 5
17.2%
N 4
13.8%
C 4
13.8%
O 4
13.8%
V 3
10.3%
T 2
 
6.9%
I 2
 
6.9%
S 1
 
3.4%
D 1
 
3.4%
B 1
 
3.4%
Other values (2) 2
 
6.9%
Common
ValueCountFrequency (%)
2 16300
72.5%
1 4777
 
21.3%
9 1381
 
6.1%
5
 
< 0.1%
- 3
 
< 0.1%
6 1
 
< 0.1%
/ 1
 
< 0.1%
8 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22498
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 16300
72.5%
1 4777
 
21.2%
9 1381
 
6.1%
A 5
 
< 0.1%
5
 
< 0.1%
N 4
 
< 0.1%
C 4
 
< 0.1%
O 4
 
< 0.1%
- 3
 
< 0.1%
V 3
 
< 0.1%
Other values (10) 12
 
0.1%

TP_FLU_AN
Categorical

HIGH CORRELATION  MISSING 

Distinct3
Distinct (%)0.1%
Missing230914
Missing (%)98.0%
Memory size9.1 MiB
1
2963 
2
1804 
86 - COVID-19 SINOVAC/BUTANTAN - CORONAVAC
 
1

Length

Max length42
Median length1
Mean length1.008599
Min length1

Characters and Unicode

Total characters4809
Distinct characters20
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row2
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 2963
 
1.3%
2 1804
 
0.8%
86 - COVID-19 SINOVAC/BUTANTAN - CORONAVAC 1
 
< 0.1%
(Missing) 230914
98.0%

Length

2023-09-22T21:42:23.290076image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:23.447624image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1 2963
62.1%
2 1804
37.8%
2
 
< 0.1%
86 1
 
< 0.1%
covid-19 1
 
< 0.1%
sinovac/butantan 1
 
< 0.1%
coronavac 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
1 2964
61.6%
2 1804
37.5%
A 5
 
0.1%
5
 
0.1%
C 4
 
0.1%
O 4
 
0.1%
N 4
 
0.1%
- 3
 
0.1%
V 3
 
0.1%
T 2
 
< 0.1%
Other values (10) 11
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4771
99.2%
Uppercase Letter 29
 
0.6%
Space Separator 5
 
0.1%
Dash Punctuation 3
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 5
17.2%
C 4
13.8%
O 4
13.8%
N 4
13.8%
V 3
10.3%
T 2
 
6.9%
I 2
 
6.9%
U 1
 
3.4%
B 1
 
3.4%
D 1
 
3.4%
Other values (2) 2
 
6.9%
Decimal Number
ValueCountFrequency (%)
1 2964
62.1%
2 1804
37.8%
9 1
 
< 0.1%
6 1
 
< 0.1%
8 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4780
99.4%
Latin 29
 
0.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 5
17.2%
C 4
13.8%
O 4
13.8%
N 4
13.8%
V 3
10.3%
T 2
 
6.9%
I 2
 
6.9%
U 1
 
3.4%
B 1
 
3.4%
D 1
 
3.4%
Other values (2) 2
 
6.9%
Common
ValueCountFrequency (%)
1 2964
62.0%
2 1804
37.7%
5
 
0.1%
- 3
 
0.1%
/ 1
 
< 0.1%
9 1
 
< 0.1%
6 1
 
< 0.1%
8 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4809
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2964
61.6%
2 1804
37.5%
A 5
 
0.1%
5
 
0.1%
C 4
 
0.1%
O 4
 
0.1%
N 4
 
0.1%
- 3
 
0.1%
V 3
 
0.1%
T 2
 
< 0.1%
Other values (10) 11
 
0.2%

POS_AN_OUT
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct3
Distinct (%)< 0.1%
Missing210238
Missing (%)89.2%
Memory size9.5 MiB
1.0
21178 
2.0
3982 
9.0
 
284

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters76332
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 21178
 
9.0%
2.0 3982
 
1.7%
9.0 284
 
0.1%
(Missing) 210238
89.2%

Length

2023-09-22T21:42:23.592242image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:23.766408image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1.0 21178
83.2%
2.0 3982
 
15.7%
9.0 284
 
1.1%

Most occurring characters

ValueCountFrequency (%)
. 25444
33.3%
0 25444
33.3%
1 21178
27.7%
2 3982
 
5.2%
9 284
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 50888
66.7%
Other Punctuation 25444
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 25444
50.0%
1 21178
41.6%
2 3982
 
7.8%
9 284
 
0.6%
Other Punctuation
ValueCountFrequency (%)
. 25444
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 76332
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 25444
33.3%
0 25444
33.3%
1 21178
27.7%
2 3982
 
5.2%
9 284
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 76332
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 25444
33.3%
0 25444
33.3%
1 21178
27.7%
2 3982
 
5.2%
9 284
 
0.4%

AN_SARS2
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct3
Distinct (%)< 0.1%
Missing219889
Missing (%)93.3%
Memory size9.3 MiB
1
15791 
86 - COVID-19 SINOVAC/BUTANTAN - CORONAVAC
 
1
2
 
1

Length

Max length42
Median length1
Mean length1.0025961
Min length1

Characters and Unicode

Total characters15834
Distinct characters20
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 15791
 
6.7%
86 - COVID-19 SINOVAC/BUTANTAN - CORONAVAC 1
 
< 0.1%
2 1
 
< 0.1%
(Missing) 219889
93.3%

Length

2023-09-22T21:42:23.923593image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:24.110907image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1 15791
> 99.9%
2
 
< 0.1%
86 1
 
< 0.1%
covid-19 1
 
< 0.1%
sinovac/butantan 1
 
< 0.1%
coronavac 1
 
< 0.1%
2 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
1 15792
99.7%
5
 
< 0.1%
A 5
 
< 0.1%
C 4
 
< 0.1%
O 4
 
< 0.1%
N 4
 
< 0.1%
- 3
 
< 0.1%
V 3
 
< 0.1%
I 2
 
< 0.1%
T 2
 
< 0.1%
Other values (10) 10
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15796
99.8%
Uppercase Letter 29
 
0.2%
Space Separator 5
 
< 0.1%
Dash Punctuation 3
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 5
17.2%
C 4
13.8%
O 4
13.8%
N 4
13.8%
V 3
10.3%
I 2
 
6.9%
T 2
 
6.9%
R 1
 
3.4%
U 1
 
3.4%
B 1
 
3.4%
Other values (2) 2
 
6.9%
Decimal Number
ValueCountFrequency (%)
1 15792
> 99.9%
9 1
 
< 0.1%
8 1
 
< 0.1%
6 1
 
< 0.1%
2 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15805
99.8%
Latin 29
 
0.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 5
17.2%
C 4
13.8%
O 4
13.8%
N 4
13.8%
V 3
10.3%
I 2
 
6.9%
T 2
 
6.9%
R 1
 
3.4%
U 1
 
3.4%
B 1
 
3.4%
Other values (2) 2
 
6.9%
Common
ValueCountFrequency (%)
1 15792
99.9%
5
 
< 0.1%
- 3
 
< 0.1%
/ 1
 
< 0.1%
9 1
 
< 0.1%
8 1
 
< 0.1%
6 1
 
< 0.1%
2 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15834
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15792
99.7%
5
 
< 0.1%
A 5
 
< 0.1%
C 4
 
< 0.1%
O 4
 
< 0.1%
N 4
 
< 0.1%
- 3
 
< 0.1%
V 3
 
< 0.1%
I 2
 
< 0.1%
T 2
 
< 0.1%
Other values (10) 10
 
0.1%

AN_VSR
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing230511
Missing (%)97.8%
Memory size9.1 MiB
1.0
5170 
210375.0
 
1

Length

Max length8
Median length3
Mean length3.0009669
Min length3

Characters and Unicode

Total characters15518
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 5170
 
2.2%
210375.0 1
 
< 0.1%
(Missing) 230511
97.8%

Length

2023-09-22T21:42:24.262263image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:24.433332image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1.0 5170
> 99.9%
210375.0 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 5172
33.3%
1 5171
33.3%
. 5171
33.3%
2 1
 
< 0.1%
3 1
 
< 0.1%
7 1
 
< 0.1%
5 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10347
66.7%
Other Punctuation 5171
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5172
50.0%
1 5171
50.0%
2 1
 
< 0.1%
3 1
 
< 0.1%
7 1
 
< 0.1%
5 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 5171
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15518
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5172
33.3%
1 5171
33.3%
. 5171
33.3%
2 1
 
< 0.1%
3 1
 
< 0.1%
7 1
 
< 0.1%
5 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15518
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5172
33.3%
1 5171
33.3%
. 5171
33.3%
2 1
 
< 0.1%
3 1
 
< 0.1%
7 1
 
< 0.1%
5 1
 
< 0.1%

AN_PARA1
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct2
Distinct (%)5.6%
Missing235646
Missing (%)> 99.9%
Memory size9.0 MiB
1.0
35 
210418.0
 
1

Length

Max length8
Median length3
Mean length3.1388889
Min length3

Characters and Unicode

Total characters113
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)2.8%

Sample

1st row1.0
2nd row210418.0
3rd row1.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 35
 
< 0.1%
210418.0 1
 
< 0.1%
(Missing) 235646
> 99.9%

Length

2023-09-22T21:42:24.578118image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:24.778780image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1.0 35
97.2%
210418.0 1
 
2.8%

Most occurring characters

ValueCountFrequency (%)
1 37
32.7%
0 37
32.7%
. 36
31.9%
2 1
 
0.9%
4 1
 
0.9%
8 1
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 77
68.1%
Other Punctuation 36
31.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 37
48.1%
0 37
48.1%
2 1
 
1.3%
4 1
 
1.3%
8 1
 
1.3%
Other Punctuation
ValueCountFrequency (%)
. 36
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 113
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 37
32.7%
0 37
32.7%
. 36
31.9%
2 1
 
0.9%
4 1
 
0.9%
8 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 113
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 37
32.7%
0 37
32.7%
. 36
31.9%
2 1
 
0.9%
4 1
 
0.9%
8 1
 
0.9%

AN_PARA2
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)8.3%
Missing235670
Missing (%)> 99.9%
Memory size9.0 MiB
1.0
12 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters36
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 12
 
< 0.1%
(Missing) 235670
> 99.9%

Length

2023-09-22T21:42:24.944340image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:25.108962image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1.0 12
100.0%

Most occurring characters

ValueCountFrequency (%)
1 12
33.3%
. 12
33.3%
0 12
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24
66.7%
Other Punctuation 12
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12
50.0%
0 12
50.0%
Other Punctuation
ValueCountFrequency (%)
. 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 36
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
33.3%
. 12
33.3%
0 12
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 36
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12
33.3%
. 12
33.3%
0 12
33.3%

AN_PARA3
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct2
Distinct (%)5.7%
Missing235647
Missing (%)> 99.9%
Memory size9.0 MiB
1.0
33 
2.0
 
2

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters105
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row2.0
3rd row1.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 33
 
< 0.1%
2.0 2
 
< 0.1%
(Missing) 235647
> 99.9%

Length

2023-09-22T21:42:25.244337image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:25.420149image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1.0 33
94.3%
2.0 2
 
5.7%

Most occurring characters

ValueCountFrequency (%)
. 35
33.3%
0 35
33.3%
1 33
31.4%
2 2
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 70
66.7%
Other Punctuation 35
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 35
50.0%
1 33
47.1%
2 2
 
2.9%
Other Punctuation
ValueCountFrequency (%)
. 35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 105
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 35
33.3%
0 35
33.3%
1 33
31.4%
2 2
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 105
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 35
33.3%
0 35
33.3%
1 33
31.4%
2 2
 
1.9%

AN_ADENO
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct2
Distinct (%)4.3%
Missing235635
Missing (%)> 99.9%
Memory size9.0 MiB
1.0
46 
2.0
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters141
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)2.1%

Sample

1st row1.0
2nd row2.0
3rd row1.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 46
 
< 0.1%
2.0 1
 
< 0.1%
(Missing) 235635
> 99.9%

Length

2023-09-22T21:42:25.577740image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:25.740562image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1.0 46
97.9%
2.0 1
 
2.1%

Most occurring characters

ValueCountFrequency (%)
. 47
33.3%
0 47
33.3%
1 46
32.6%
2 1
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 94
66.7%
Other Punctuation 47
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 47
50.0%
1 46
48.9%
2 1
 
1.1%
Other Punctuation
ValueCountFrequency (%)
. 47
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 141
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 47
33.3%
0 47
33.3%
1 46
32.6%
2 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 141
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 47
33.3%
0 47
33.3%
1 46
32.6%
2 1
 
0.7%

AN_OUTRO
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.4%
Missing235403
Missing (%)99.9%
Memory size9.0 MiB
1.0
279 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters837
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 279
 
0.1%
(Missing) 235403
99.9%

Length

2023-09-22T21:42:25.873537image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:26.050350image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1.0 279
100.0%

Most occurring characters

ValueCountFrequency (%)
1 279
33.3%
. 279
33.3%
0 279
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 558
66.7%
Other Punctuation 279
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 279
50.0%
0 279
50.0%
Other Punctuation
ValueCountFrequency (%)
. 279
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 837
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 279
33.3%
. 279
33.3%
0 279
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 837
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 279
33.3%
. 279
33.3%
0 279
33.3%

DS_AN_OUT
Text

MISSING 

Distinct51
Distinct (%)20.0%
Missing235427
Missing (%)99.9%
Memory size7.2 MiB
2023-09-22T21:42:26.266896image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length30
Median length28
Mean length11.792157
Min length3

Characters and Unicode

Total characters3007
Distinct characters35
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)11.4%

Sample

1st rowCOVID-19
2nd rowSRAG
3rd rowCOVID-19
4th row29/01/2021
5th rowMETAPNEUMOVIRUS HUMANO
ValueCountFrequency (%)
influenza 71
18.6%
b 65
17.0%
rinovirus 50
13.1%
rhinovirus 36
 
9.4%
metapneumovirus 21
 
5.5%
h1n1 11
 
2.9%
bocavirus 10
 
2.6%
sincicial 9
 
2.4%
enterovirus 9
 
2.4%
covid-19 8
 
2.1%
Other values (45) 92
24.1%
2023-09-22T21:42:26.756167image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
I 391
13.0%
N 326
10.8%
R 305
10.1%
U 273
9.1%
O 195
 
6.5%
S 188
 
6.3%
E 180
 
6.0%
V 179
 
6.0%
A 161
 
5.4%
129
 
4.3%
Other values (25) 680
22.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 2789
92.8%
Space Separator 129
 
4.3%
Decimal Number 61
 
2.0%
Other Punctuation 18
 
0.6%
Dash Punctuation 8
 
0.3%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
I 391
14.0%
N 326
11.7%
R 305
10.9%
U 273
9.8%
O 195
 
7.0%
S 188
 
6.7%
E 180
 
6.5%
V 179
 
6.4%
A 161
 
5.8%
L 86
 
3.1%
Other values (12) 505
18.1%
Decimal Number
ValueCountFrequency (%)
1 32
52.5%
9 10
 
16.4%
4 5
 
8.2%
3 5
 
8.2%
2 4
 
6.6%
0 4
 
6.6%
6 1
 
1.6%
Other Punctuation
ValueCountFrequency (%)
/ 12
66.7%
, 6
33.3%
Space Separator
ValueCountFrequency (%)
129
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2789
92.8%
Common 218
 
7.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
I 391
14.0%
N 326
11.7%
R 305
10.9%
U 273
9.8%
O 195
 
7.0%
S 188
 
6.7%
E 180
 
6.5%
V 179
 
6.4%
A 161
 
5.8%
L 86
 
3.1%
Other values (12) 505
18.1%
Common
ValueCountFrequency (%)
129
59.2%
1 32
 
14.7%
/ 12
 
5.5%
9 10
 
4.6%
- 8
 
3.7%
, 6
 
2.8%
4 5
 
2.3%
3 5
 
2.3%
2 4
 
1.8%
0 4
 
1.8%
Other values (3) 3
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3007
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
I 391
13.0%
N 326
10.8%
R 305
10.1%
U 273
9.1%
O 195
 
6.5%
S 188
 
6.3%
E 180
 
6.0%
V 179
 
6.0%
A 161
 
5.4%
129
 
4.3%
Other values (25) 680
22.6%

TP_AM_SOR
Categorical

HIGH CORRELATION  MISSING 

Distinct3
Distinct (%)< 0.1%
Missing227683
Missing (%)96.6%
Memory size9.1 MiB
9.0
4608 
1.0
1856 
2.0
1535 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters23997
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2.0
2nd row9.0
3rd row9.0
4th row9.0
5th row9.0

Common Values

ValueCountFrequency (%)
9.0 4608
 
2.0%
1.0 1856
 
0.8%
2.0 1535
 
0.7%
(Missing) 227683
96.6%

Length

2023-09-22T21:42:26.964874image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:27.140972image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
9.0 4608
57.6%
1.0 1856
23.2%
2.0 1535
 
19.2%

Most occurring characters

ValueCountFrequency (%)
. 7999
33.3%
0 7999
33.3%
9 4608
19.2%
1 1856
 
7.7%
2 1535
 
6.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15998
66.7%
Other Punctuation 7999
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7999
50.0%
9 4608
28.8%
1 1856
 
11.6%
2 1535
 
9.6%
Other Punctuation
ValueCountFrequency (%)
. 7999
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 23997
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 7999
33.3%
0 7999
33.3%
9 4608
19.2%
1 1856
 
7.7%
2 1535
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23997
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 7999
33.3%
0 7999
33.3%
9 4608
19.2%
1 1856
 
7.7%
2 1535
 
6.4%

SOR_OUT
Text

MISSING 

Distinct144
Distinct (%)9.2%
Missing234123
Missing (%)99.3%
Memory size7.3 MiB
2023-09-22T21:42:27.364733image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length49
Median length28
Mean length13.907633
Min length1

Characters and Unicode

Total characters21682
Distinct characters33
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique75 ?
Unique (%)4.8%

Sample

1st rowSWAB
2nd rowSWAB DE NASOFARINGE E OROFARINGE
3rd rowNASOFARINGEA
4th rowSWAB
5th rowSWAB NASO
ValueCountFrequency (%)
swab 495
19.4%
naso-orofaringe 321
12.6%
nasofaringe 317
12.4%
secrecao 312
12.2%
nasal 179
 
7.0%
naso 150
 
5.9%
nasofaringeo 139
 
5.4%
nasofaringea 77
 
3.0%
de 64
 
2.5%
orofaringe 61
 
2.4%
Other values (94) 442
17.3%
2023-09-22T21:42:27.848419image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 3583
16.5%
O 2609
12.0%
N 2296
10.6%
S 2159
10.0%
R 2024
9.3%
E 1906
8.8%
I 1146
 
5.3%
F 1035
 
4.8%
G 1034
 
4.8%
999
 
4.6%
Other values (23) 2891
13.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 20280
93.5%
Space Separator 999
 
4.6%
Dash Punctuation 385
 
1.8%
Decimal Number 11
 
0.1%
Other Punctuation 6
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 3583
17.7%
O 2609
12.9%
N 2296
11.3%
S 2159
10.6%
R 2024
10.0%
E 1906
9.4%
I 1146
 
5.7%
F 1035
 
5.1%
G 1034
 
5.1%
C 698
 
3.4%
Other values (13) 1790
8.8%
Decimal Number
ValueCountFrequency (%)
2 6
54.5%
0 2
 
18.2%
1 1
 
9.1%
8 1
 
9.1%
3 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
/ 5
83.3%
: 1
 
16.7%
Space Separator
ValueCountFrequency (%)
999
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 385
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 20280
93.5%
Common 1402
 
6.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 3583
17.7%
O 2609
12.9%
N 2296
11.3%
S 2159
10.6%
R 2024
10.0%
E 1906
9.4%
I 1146
 
5.7%
F 1035
 
5.1%
G 1034
 
5.1%
C 698
 
3.4%
Other values (13) 1790
8.8%
Common
ValueCountFrequency (%)
999
71.3%
- 385
 
27.5%
2 6
 
0.4%
/ 5
 
0.4%
0 2
 
0.1%
~ 1
 
0.1%
: 1
 
0.1%
1 1
 
0.1%
8 1
 
0.1%
3 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21682
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 3583
16.5%
O 2609
12.0%
N 2296
10.6%
S 2159
10.0%
R 2024
9.3%
E 1906
8.8%
I 1146
 
5.3%
F 1035
 
4.8%
G 1034
 
4.8%
999
 
4.6%
Other values (23) 2891
13.3%

DT_CO_SOR
Text

MISSING 

Distinct268
Distinct (%)5.3%
Missing230631
Missing (%)97.9%
Memory size7.4 MiB
2023-09-22T21:42:28.177671image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length42
Median length10
Mean length10.006137
Min length9

Characters and Unicode

Total characters50541
Distinct characters25
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)0.2%

Sample

1st row01/01/2023
2nd row06/01/2023
3rd row20/01/2023
4th row22/02/2023
5th row23/03/2023
ValueCountFrequency (%)
23/05/2023 47
 
0.9%
10/05/2023 46
 
0.9%
22/03/2023 44
 
0.9%
31/05/2023 43
 
0.9%
29/05/2023 43
 
0.9%
30/05/2023 42
 
0.8%
02/06/2023 41
 
0.8%
05/06/2023 40
 
0.8%
22/06/2023 39
 
0.8%
06/06/2023 38
 
0.8%
Other values (262) 4633
91.6%
2023-09-22T21:42:28.690456image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 12740
25.2%
0 12086
23.9%
/ 10101
20.0%
3 6544
12.9%
1 2592
 
5.1%
5 1451
 
2.9%
6 1233
 
2.4%
4 1211
 
2.4%
7 1097
 
2.2%
8 844
 
1.7%
Other values (15) 642
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 40403
79.9%
Other Punctuation 10101
 
20.0%
Uppercase Letter 29
 
0.1%
Space Separator 5
 
< 0.1%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 5
17.2%
N 4
13.8%
C 4
13.8%
O 4
13.8%
V 3
10.3%
I 2
 
6.9%
T 2
 
6.9%
D 1
 
3.4%
S 1
 
3.4%
B 1
 
3.4%
Other values (2) 2
 
6.9%
Decimal Number
ValueCountFrequency (%)
2 12740
31.5%
0 12086
29.9%
3 6544
16.2%
1 2592
 
6.4%
5 1451
 
3.6%
6 1233
 
3.1%
4 1211
 
3.0%
7 1097
 
2.7%
8 844
 
2.1%
9 605
 
1.5%
Other Punctuation
ValueCountFrequency (%)
/ 10101
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 50512
99.9%
Latin 29
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
2 12740
25.2%
0 12086
23.9%
/ 10101
20.0%
3 6544
13.0%
1 2592
 
5.1%
5 1451
 
2.9%
6 1233
 
2.4%
4 1211
 
2.4%
7 1097
 
2.2%
8 844
 
1.7%
Other values (3) 613
 
1.2%
Latin
ValueCountFrequency (%)
A 5
17.2%
N 4
13.8%
C 4
13.8%
O 4
13.8%
V 3
10.3%
I 2
 
6.9%
T 2
 
6.9%
D 1
 
3.4%
S 1
 
3.4%
B 1
 
3.4%
Other values (2) 2
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 50541
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 12740
25.2%
0 12086
23.9%
/ 10101
20.0%
3 6544
12.9%
1 2592
 
5.1%
5 1451
 
2.9%
6 1233
 
2.4%
4 1211
 
2.4%
7 1097
 
2.2%
8 844
 
1.7%
Other values (15) 642
 
1.3%

TP_SOR
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct5
Distinct (%)0.1%
Missing232167
Missing (%)98.5%
Memory size9.1 MiB
1
2781 
4
606 
3
 
69
2
 
58
16/04/2021
 
1

Length

Max length10
Median length1
Mean length1.0025605
Min length1

Characters and Unicode

Total characters3524
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 2781
 
1.2%
4 606
 
0.3%
3 69
 
< 0.1%
2 58
 
< 0.1%
16/04/2021 1
 
< 0.1%
(Missing) 232167
98.5%

Length

2023-09-22T21:42:28.891627image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:29.178976image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1 2781
79.1%
4 606
 
17.2%
3 69
 
2.0%
2 58
 
1.7%
16/04/2021 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
1 2783
79.0%
4 607
 
17.2%
3 69
 
2.0%
2 60
 
1.7%
/ 2
 
0.1%
0 2
 
0.1%
6 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3522
99.9%
Other Punctuation 2
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2783
79.0%
4 607
 
17.2%
3 69
 
2.0%
2 60
 
1.7%
0 2
 
0.1%
6 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
/ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3524
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2783
79.0%
4 607
 
17.2%
3 69
 
2.0%
2 60
 
1.7%
/ 2
 
0.1%
0 2
 
0.1%
6 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3524
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2783
79.0%
4 607
 
17.2%
3 69
 
2.0%
2 60
 
1.7%
/ 2
 
0.1%
0 2
 
0.1%
6 1
 
< 0.1%

OUT_SOR
Text

MISSING 

Distinct63
Distinct (%)10.1%
Missing235059
Missing (%)99.7%
Memory size7.2 MiB
2023-09-22T21:42:29.597003image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length59
Median length6
Mean length8.0722311
Min length1

Characters and Unicode

Total characters5029
Distinct characters39
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)5.6%

Sample

1st rowRT PCR
2nd rowRT-PCR
3rd rowIMUNOCROMATOGRAFICO.
4th rowRT-PCR
5th rowRT-PCR
ValueCountFrequency (%)
rt-pcr 335
40.4%
pcr 110
 
13.3%
rt 101
 
12.2%
swab 47
 
5.7%
imunocromatografico 33
 
4.0%
molecular 14
 
1.7%
naso 12
 
1.4%
covid-19 11
 
1.3%
nasofaringeo 10
 
1.2%
rtpcr 8
 
1.0%
Other values (72) 148
17.9%
2023-09-22T21:42:30.503328image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
R 1076
21.4%
C 588
11.7%
T 531
10.6%
P 481
9.6%
- 357
 
7.1%
O 302
 
6.0%
A 277
 
5.5%
208
 
4.1%
I 188
 
3.7%
N 147
 
2.9%
Other values (29) 874
17.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 4382
87.1%
Dash Punctuation 357
 
7.1%
Space Separator 208
 
4.1%
Other Punctuation 39
 
0.8%
Decimal Number 37
 
0.7%
Open Punctuation 3
 
0.1%
Close Punctuation 3
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R 1076
24.6%
C 588
13.4%
T 531
12.1%
P 481
11.0%
O 302
 
6.9%
A 277
 
6.3%
I 188
 
4.3%
N 147
 
3.4%
E 122
 
2.8%
S 113
 
2.6%
Other values (15) 557
12.7%
Decimal Number
ValueCountFrequency (%)
1 12
32.4%
9 11
29.7%
2 5
13.5%
0 4
 
10.8%
4 3
 
8.1%
7 1
 
2.7%
3 1
 
2.7%
Other Punctuation
ValueCountFrequency (%)
. 28
71.8%
/ 6
 
15.4%
, 5
 
12.8%
Dash Punctuation
ValueCountFrequency (%)
- 357
100.0%
Space Separator
ValueCountFrequency (%)
208
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4382
87.1%
Common 647
 
12.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
R 1076
24.6%
C 588
13.4%
T 531
12.1%
P 481
11.0%
O 302
 
6.9%
A 277
 
6.3%
I 188
 
4.3%
N 147
 
3.4%
E 122
 
2.8%
S 113
 
2.6%
Other values (15) 557
12.7%
Common
ValueCountFrequency (%)
- 357
55.2%
208
32.1%
. 28
 
4.3%
1 12
 
1.9%
9 11
 
1.7%
/ 6
 
0.9%
2 5
 
0.8%
, 5
 
0.8%
0 4
 
0.6%
( 3
 
0.5%
Other values (4) 8
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5029
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
R 1076
21.4%
C 588
11.7%
T 531
10.6%
P 481
9.6%
- 357
 
7.1%
O 302
 
6.0%
A 277
 
5.5%
208
 
4.1%
I 188
 
3.7%
N 147
 
2.9%
Other values (29) 874
17.4%

DT_RES
Text

MISSING 

Distinct267
Distinct (%)6.8%
Missing231762
Missing (%)98.3%
Memory size7.3 MiB
2023-09-22T21:42:31.047400image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length42
Median length10
Mean length10.005867
Min length1

Characters and Unicode

Total characters39223
Distinct characters25
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)0.3%

Sample

1st row01/01/2023
2nd row06/01/2023
3rd row26/01/2023
4th row24/02/2023
5th row11/03/2023
ValueCountFrequency (%)
03/05/2023 64
 
1.6%
12/04/2023 62
 
1.6%
25/04/2023 46
 
1.2%
14/06/2023 46
 
1.2%
31/05/2023 45
 
1.1%
20/04/2023 45
 
1.1%
23/05/2023 42
 
1.1%
22/06/2023 40
 
1.0%
07/06/2023 40
 
1.0%
19/05/2023 39
 
1.0%
Other values (261) 3456
88.1%
2023-09-22T21:42:31.630946image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 9893
25.2%
0 9378
23.9%
/ 7837
20.0%
3 5140
13.1%
1 2015
 
5.1%
5 1191
 
3.0%
4 996
 
2.5%
6 918
 
2.3%
7 766
 
2.0%
8 650
 
1.7%
Other values (15) 439
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31349
79.9%
Other Punctuation 7837
 
20.0%
Uppercase Letter 29
 
0.1%
Space Separator 5
 
< 0.1%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 5
17.2%
N 4
13.8%
C 4
13.8%
O 4
13.8%
V 3
10.3%
I 2
 
6.9%
T 2
 
6.9%
D 1
 
3.4%
S 1
 
3.4%
B 1
 
3.4%
Other values (2) 2
 
6.9%
Decimal Number
ValueCountFrequency (%)
2 9893
31.6%
0 9378
29.9%
3 5140
16.4%
1 2015
 
6.4%
5 1191
 
3.8%
4 996
 
3.2%
6 918
 
2.9%
7 766
 
2.4%
8 650
 
2.1%
9 402
 
1.3%
Other Punctuation
ValueCountFrequency (%)
/ 7837
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39194
99.9%
Latin 29
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
2 9893
25.2%
0 9378
23.9%
/ 7837
20.0%
3 5140
13.1%
1 2015
 
5.1%
5 1191
 
3.0%
4 996
 
2.5%
6 918
 
2.3%
7 766
 
2.0%
8 650
 
1.7%
Other values (3) 410
 
1.0%
Latin
ValueCountFrequency (%)
A 5
17.2%
N 4
13.8%
C 4
13.8%
O 4
13.8%
V 3
10.3%
I 2
 
6.9%
T 2
 
6.9%
D 1
 
3.4%
S 1
 
3.4%
B 1
 
3.4%
Other values (2) 2
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39223
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 9893
25.2%
0 9378
23.9%
/ 7837
20.0%
3 5140
13.1%
1 2015
 
5.1%
5 1191
 
3.0%
4 996
 
2.5%
6 918
 
2.3%
7 766
 
2.0%
8 650
 
1.7%
Other values (15) 439
 
1.1%

RES_IGG
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct8
Distinct (%)< 0.1%
Missing215951
Missing (%)91.6%
Memory size9.3 MiB
4
17712 
2
 
872
9
 
804
1
 
292
5
 
33
Other values (3)
 
18

Length

Max length42
Median length1
Mean length1.0024834
Min length1

Characters and Unicode

Total characters19780
Distinct characters24
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row4
2nd row4
3rd row4
4th row4
5th row4

Common Values

ValueCountFrequency (%)
4 17712
 
7.5%
2 872
 
0.4%
9 804
 
0.3%
1 292
 
0.1%
5 33
 
< 0.1%
3 16
 
< 0.1%
202010033 1
 
< 0.1%
86 - COVID-19 SINOVAC/BUTANTAN - CORONAVAC 1
 
< 0.1%
(Missing) 215951
91.6%

Length

2023-09-22T21:42:31.834251image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:32.024982image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
4 17712
89.7%
2 872
 
4.4%
9 804
 
4.1%
1 292
 
1.5%
5 33
 
0.2%
3 16
 
0.1%
2
 
< 0.1%
202010033 1
 
< 0.1%
86 1
 
< 0.1%
covid-19 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
4 17712
89.5%
2 874
 
4.4%
9 805
 
4.1%
1 294
 
1.5%
5 33
 
0.2%
3 18
 
0.1%
A 5
 
< 0.1%
5
 
< 0.1%
C 4
 
< 0.1%
N 4
 
< 0.1%
Other values (14) 26
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 19742
99.8%
Uppercase Letter 29
 
0.1%
Space Separator 5
 
< 0.1%
Dash Punctuation 3
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 5
17.2%
C 4
13.8%
N 4
13.8%
O 4
13.8%
V 3
10.3%
I 2
 
6.9%
T 2
 
6.9%
D 1
 
3.4%
S 1
 
3.4%
B 1
 
3.4%
Other values (2) 2
 
6.9%
Decimal Number
ValueCountFrequency (%)
4 17712
89.7%
2 874
 
4.4%
9 805
 
4.1%
1 294
 
1.5%
5 33
 
0.2%
3 18
 
0.1%
0 4
 
< 0.1%
6 1
 
< 0.1%
8 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19751
99.9%
Latin 29
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
4 17712
89.7%
2 874
 
4.4%
9 805
 
4.1%
1 294
 
1.5%
5 33
 
0.2%
3 18
 
0.1%
5
 
< 0.1%
0 4
 
< 0.1%
- 3
 
< 0.1%
6 1
 
< 0.1%
Other values (2) 2
 
< 0.1%
Latin
ValueCountFrequency (%)
A 5
17.2%
C 4
13.8%
N 4
13.8%
O 4
13.8%
V 3
10.3%
I 2
 
6.9%
T 2
 
6.9%
D 1
 
3.4%
S 1
 
3.4%
B 1
 
3.4%
Other values (2) 2
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19780
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 17712
89.5%
2 874
 
4.4%
9 805
 
4.1%
1 294
 
1.5%
5 33
 
0.2%
3 18
 
0.1%
A 5
 
< 0.1%
5
 
< 0.1%
C 4
 
< 0.1%
N 4
 
< 0.1%
Other values (14) 26
 
0.1%

RES_IGM
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct8
Distinct (%)< 0.1%
Missing215751
Missing (%)91.5%
Memory size9.3 MiB
4
17575 
2
 
1182
9
 
791
1
 
323
5
 
38
Other values (3)
 
22

Length

Max length32
Median length1
Mean length1.0019568
Min length1

Characters and Unicode

Total characters19970
Distinct characters29
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row4
2nd row4
3rd row4
4th row4
5th row4

Common Values

ValueCountFrequency (%)
4 17575
 
7.5%
2 1182
 
0.5%
9 791
 
0.3%
1 323
 
0.1%
5 38
 
< 0.1%
3 20
 
< 0.1%
VISHIELD" 1
 
< 0.1%
87 - COVID-19 PFIZER - COMIRNATY 1
 
< 0.1%
(Missing) 215751
91.5%

Length

2023-09-22T21:42:32.225701image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:32.428331image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
4 17575
88.2%
2 1182
 
5.9%
9 791
 
4.0%
1 323
 
1.6%
5 38
 
0.2%
3 20
 
0.1%
2
 
< 0.1%
vishield 1
 
< 0.1%
87 1
 
< 0.1%
covid-19 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
4 17575
88.0%
2 1182
 
5.9%
9 792
 
4.0%
1 324
 
1.6%
5 38
 
0.2%
3 20
 
0.1%
I 5
 
< 0.1%
5
 
< 0.1%
- 3
 
< 0.1%
O 2
 
< 0.1%
Other values (19) 24
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 19933
99.8%
Uppercase Letter 28
 
0.1%
Space Separator 5
 
< 0.1%
Dash Punctuation 3
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
I 5
17.9%
O 2
 
7.1%
C 2
 
7.1%
R 2
 
7.1%
E 2
 
7.1%
D 2
 
7.1%
V 2
 
7.1%
M 1
 
3.6%
N 1
 
3.6%
F 1
 
3.6%
Other values (8) 8
28.6%
Decimal Number
ValueCountFrequency (%)
4 17575
88.2%
2 1182
 
5.9%
9 792
 
4.0%
1 324
 
1.6%
5 38
 
0.2%
3 20
 
0.1%
8 1
 
< 0.1%
7 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Punctuation
ValueCountFrequency (%)
" 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19942
99.9%
Latin 28
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
I 5
17.9%
O 2
 
7.1%
C 2
 
7.1%
R 2
 
7.1%
E 2
 
7.1%
D 2
 
7.1%
V 2
 
7.1%
M 1
 
3.6%
N 1
 
3.6%
F 1
 
3.6%
Other values (8) 8
28.6%
Common
ValueCountFrequency (%)
4 17575
88.1%
2 1182
 
5.9%
9 792
 
4.0%
1 324
 
1.6%
5 38
 
0.2%
3 20
 
0.1%
5
 
< 0.1%
- 3
 
< 0.1%
8 1
 
< 0.1%
7 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19970
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 17575
88.0%
2 1182
 
5.9%
9 792
 
4.0%
1 324
 
1.6%
5 38
 
0.2%
3 20
 
0.1%
I 5
 
< 0.1%
5
 
< 0.1%
- 3
 
< 0.1%
O 2
 
< 0.1%
Other values (19) 24
 
0.1%

RES_IGA
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct9
Distinct (%)< 0.1%
Missing216438
Missing (%)91.8%
Memory size9.3 MiB
4
17562 
9
 
833
2
 
704
1
 
72
5
 
53
Other values (4)
 
20

Length

Max length10
Median length1
Mean length1.0011952
Min length1

Characters and Unicode

Total characters19267
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row4
2nd row4
3rd row4
4th row4
5th row4

Common Values

ValueCountFrequency (%)
4 17562
 
7.5%
9 833
 
0.4%
2 704
 
0.3%
1 72
 
< 0.1%
5 53
 
< 0.1%
3 17
 
< 0.1%
GF9674 1
 
< 0.1%
21OVCD330Z 1
 
< 0.1%
13/03/2021 1
 
< 0.1%
(Missing) 216438
91.8%

Length

2023-09-22T21:42:32.609714image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:32.813047image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
4 17562
91.3%
9 833
 
4.3%
2 704
 
3.7%
1 72
 
0.4%
5 53
 
0.3%
3 17
 
0.1%
gf9674 1
 
< 0.1%
21ovcd330z 1
 
< 0.1%
13/03/2021 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
4 17563
91.2%
9 834
 
4.3%
2 707
 
3.7%
1 75
 
0.4%
5 53
 
0.3%
3 21
 
0.1%
0 3
 
< 0.1%
/ 2
 
< 0.1%
F 1
 
< 0.1%
7 1
 
< 0.1%
Other values (7) 7
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 19258
> 99.9%
Uppercase Letter 7
 
< 0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 17563
91.2%
9 834
 
4.3%
2 707
 
3.7%
1 75
 
0.4%
5 53
 
0.3%
3 21
 
0.1%
0 3
 
< 0.1%
7 1
 
< 0.1%
6 1
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
F 1
14.3%
O 1
14.3%
V 1
14.3%
C 1
14.3%
D 1
14.3%
G 1
14.3%
Z 1
14.3%
Other Punctuation
ValueCountFrequency (%)
/ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19260
> 99.9%
Latin 7
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
4 17563
91.2%
9 834
 
4.3%
2 707
 
3.7%
1 75
 
0.4%
5 53
 
0.3%
3 21
 
0.1%
0 3
 
< 0.1%
/ 2
 
< 0.1%
7 1
 
< 0.1%
6 1
 
< 0.1%
Latin
ValueCountFrequency (%)
F 1
14.3%
O 1
14.3%
V 1
14.3%
C 1
14.3%
D 1
14.3%
G 1
14.3%
Z 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19267
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 17563
91.2%
9 834
 
4.3%
2 707
 
3.7%
1 75
 
0.4%
5 53
 
0.3%
3 21
 
0.1%
0 3
 
< 0.1%
/ 2
 
< 0.1%
F 1
 
< 0.1%
7 1
 
< 0.1%
Other values (7) 7
 
< 0.1%

ESTRANG
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct5
Distinct (%)< 0.1%
Missing19856
Missing (%)8.4%
Memory size12.7 MiB
2
214206 
1
 
1617
23/03/2021
 
1
05/04/2021
 
1
01/04/2021
 
1

Length

Max length10
Median length1
Mean length1.0001251
Min length1

Characters and Unicode

Total characters215853
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 214206
90.9%
1 1617
 
0.7%
23/03/2021 1
 
< 0.1%
05/04/2021 1
 
< 0.1%
01/04/2021 1
 
< 0.1%
(Missing) 19856
 
8.4%

Length

2023-09-22T21:42:32.996646image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:33.200146image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
2 214206
99.2%
1 1617
 
0.7%
23/03/2021 1
 
< 0.1%
05/04/2021 1
 
< 0.1%
01/04/2021 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
2 214213
99.2%
1 1621
 
0.8%
0 8
 
< 0.1%
/ 6
 
< 0.1%
3 2
 
< 0.1%
4 2
 
< 0.1%
5 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 215847
> 99.9%
Other Punctuation 6
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 214213
99.2%
1 1621
 
0.8%
0 8
 
< 0.1%
3 2
 
< 0.1%
4 2
 
< 0.1%
5 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
/ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 215853
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 214213
99.2%
1 1621
 
0.8%
0 8
 
< 0.1%
/ 6
 
< 0.1%
3 2
 
< 0.1%
4 2
 
< 0.1%
5 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 215853
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 214213
99.2%
1 1621
 
0.8%
0 8
 
< 0.1%
/ 6
 
< 0.1%
3 2
 
< 0.1%
4 2
 
< 0.1%
5 1
 
< 0.1%

VACINA_COV
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct8
Distinct (%)< 0.1%
Missing86
Missing (%)< 0.1%
Memory size13.0 MiB
1
117808 
2
113287 
9
 
4496
28/02/2023
 
1
14/04/2021
 
1
Other values (3)
 
3

Length

Max length10
Median length1
Mean length1.000174
Min length1

Characters and Unicode

Total characters235637
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 117808
50.0%
2 113287
48.1%
9 4496
 
1.9%
28/02/2023 1
 
< 0.1%
14/04/2021 1
 
< 0.1%
16/11/2021 1
 
< 0.1%
210108 1
 
< 0.1%
22/04/2021 1
 
< 0.1%
(Missing) 86
 
< 0.1%

Length

2023-09-22T21:42:33.366157image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:33.566317image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1 117808
50.0%
2 113287
48.1%
9 4496
 
1.9%
28/02/2023 1
 
< 0.1%
14/04/2021 1
 
< 0.1%
16/11/2021 1
 
< 0.1%
210108 1
 
< 0.1%
22/04/2021 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
1 117817
50.0%
2 113300
48.1%
9 4496
 
1.9%
0 9
 
< 0.1%
/ 8
 
< 0.1%
4 3
 
< 0.1%
8 2
 
< 0.1%
3 1
 
< 0.1%
6 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 235629
> 99.9%
Other Punctuation 8
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 117817
50.0%
2 113300
48.1%
9 4496
 
1.9%
0 9
 
< 0.1%
4 3
 
< 0.1%
8 2
 
< 0.1%
3 1
 
< 0.1%
6 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
/ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 235637
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 117817
50.0%
2 113300
48.1%
9 4496
 
1.9%
0 9
 
< 0.1%
/ 8
 
< 0.1%
4 3
 
< 0.1%
8 2
 
< 0.1%
3 1
 
< 0.1%
6 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 235637
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 117817
50.0%
2 113300
48.1%
9 4496
 
1.9%
0 9
 
< 0.1%
/ 8
 
< 0.1%
4 3
 
< 0.1%
8 2
 
< 0.1%
3 1
 
< 0.1%
6 1
 
< 0.1%

DOSE_1_COV
Text

MISSING 

Distinct904
Distinct (%)0.8%
Missing123088
Missing (%)52.2%
Memory size11.0 MiB
2023-09-22T21:42:33.881069image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length43
Median length10
Mean length10.000542
Min length6

Characters and Unicode

Total characters1126001
Distinct characters32
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)< 0.1%

Sample

1st row22/01/2021
2nd row20/04/2021
3rd row26/03/2021
4th row01/06/2021
5th row26/03/2021
ValueCountFrequency (%)
22/09/2021 2909
 
2.6%
03/03/2021 1587
 
1.4%
26/03/2021 1541
 
1.4%
01/03/2021 1437
 
1.3%
25/03/2021 1390
 
1.2%
23/03/2021 1354
 
1.2%
24/03/2021 1345
 
1.2%
19/03/2021 1330
 
1.2%
30/03/2021 1241
 
1.1%
12/02/2021 1221
 
1.1%
Other values (901) 97250
86.4%
2023-09-22T21:42:34.409794image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 315320
28.0%
0 265627
23.6%
/ 225183
20.0%
1 152038
13.5%
3 51836
 
4.6%
5 23110
 
2.1%
4 23050
 
2.0%
6 20492
 
1.8%
7 16949
 
1.5%
9 16557
 
1.5%
Other values (22) 15839
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 900741
80.0%
Other Punctuation 225183
 
20.0%
Uppercase Letter 60
 
< 0.1%
Space Separator 11
 
< 0.1%
Dash Punctuation 6
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 7
11.7%
N 6
10.0%
I 6
10.0%
C 6
10.0%
O 6
10.0%
V 5
8.3%
T 4
 
6.7%
R 3
 
5.0%
E 3
 
5.0%
B 2
 
3.3%
Other values (9) 12
20.0%
Decimal Number
ValueCountFrequency (%)
2 315320
35.0%
0 265627
29.5%
1 152038
16.9%
3 51836
 
5.8%
5 23110
 
2.6%
4 23050
 
2.6%
6 20492
 
2.3%
7 16949
 
1.9%
9 16557
 
1.8%
8 15762
 
1.7%
Other Punctuation
ValueCountFrequency (%)
/ 225183
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1125941
> 99.9%
Latin 60
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 7
11.7%
N 6
10.0%
I 6
10.0%
C 6
10.0%
O 6
10.0%
V 5
8.3%
T 4
 
6.7%
R 3
 
5.0%
E 3
 
5.0%
B 2
 
3.3%
Other values (9) 12
20.0%
Common
ValueCountFrequency (%)
2 315320
28.0%
0 265627
23.6%
/ 225183
20.0%
1 152038
13.5%
3 51836
 
4.6%
5 23110
 
2.1%
4 23050
 
2.0%
6 20492
 
1.8%
7 16949
 
1.5%
9 16557
 
1.5%
Other values (3) 15779
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1126001
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 315320
28.0%
0 265627
23.6%
/ 225183
20.0%
1 152038
13.5%
3 51836
 
4.6%
5 23110
 
2.1%
4 23050
 
2.0%
6 20492
 
1.8%
7 16949
 
1.5%
9 16557
 
1.5%
Other values (22) 15839
 
1.4%

DOSE_2_COV
Text

MISSING 

Distinct892
Distinct (%)0.9%
Missing133632
Missing (%)56.7%
Memory size10.6 MiB
2023-09-22T21:42:34.722924image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length42
Median length10
Mean length10.000813
Min length1

Characters and Unicode

Total characters1020583
Distinct characters27
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)< 0.1%

Sample

1st row10/02/2021
2nd row23/04/2021
3rd row24/08/2021
4th row19/05/2021
5th row09/08/2021
ValueCountFrequency (%)
04/06/2021 3434
 
3.4%
19/04/2021 1212
 
1.2%
20/04/2021 1194
 
1.2%
22/04/2021 1169
 
1.1%
16/04/2021 1152
 
1.1%
09/04/2021 1095
 
1.1%
26/04/2021 999
 
1.0%
23/04/2021 958
 
0.9%
05/04/2021 898
 
0.9%
15/04/2021 885
 
0.9%
Other values (886) 89069
87.3%
2023-09-22T21:42:35.203437image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 265736
26.0%
0 239466
23.5%
/ 204093
20.0%
1 144944
14.2%
4 34981
 
3.4%
3 32371
 
3.2%
5 21406
 
2.1%
8 20215
 
2.0%
7 19407
 
1.9%
6 18929
 
1.9%
Other values (17) 19035
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 816377
80.0%
Other Punctuation 204093
 
20.0%
Uppercase Letter 89
 
< 0.1%
Space Separator 15
 
< 0.1%
Dash Punctuation 9
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 15
16.9%
N 12
13.5%
C 12
13.5%
O 12
13.5%
V 9
10.1%
I 6
 
6.7%
T 6
 
6.7%
D 3
 
3.4%
S 3
 
3.4%
B 3
 
3.4%
Other values (4) 8
9.0%
Decimal Number
ValueCountFrequency (%)
2 265736
32.6%
0 239466
29.3%
1 144944
17.8%
4 34981
 
4.3%
3 32371
 
4.0%
5 21406
 
2.6%
8 20215
 
2.5%
7 19407
 
2.4%
6 18929
 
2.3%
9 18922
 
2.3%
Other Punctuation
ValueCountFrequency (%)
/ 204093
100.0%
Space Separator
ValueCountFrequency (%)
15
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1020494
> 99.9%
Latin 89
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 15
16.9%
N 12
13.5%
C 12
13.5%
O 12
13.5%
V 9
10.1%
I 6
 
6.7%
T 6
 
6.7%
D 3
 
3.4%
S 3
 
3.4%
B 3
 
3.4%
Other values (4) 8
9.0%
Common
ValueCountFrequency (%)
2 265736
26.0%
0 239466
23.5%
/ 204093
20.0%
1 144944
14.2%
4 34981
 
3.4%
3 32371
 
3.2%
5 21406
 
2.1%
8 20215
 
2.0%
7 19407
 
1.9%
6 18929
 
1.9%
Other values (3) 18946
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020583
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 265736
26.0%
0 239466
23.5%
/ 204093
20.0%
1 144944
14.2%
4 34981
 
3.4%
3 32371
 
3.2%
5 21406
 
2.1%
8 20215
 
2.0%
7 19407
 
1.9%
6 18929
 
1.9%
Other values (17) 19035
 
1.9%

DOSE_REF
Text

MISSING 

Distinct640
Distinct (%)0.9%
Missing167838
Missing (%)71.2%
Memory size9.5 MiB
2023-09-22T21:42:35.560611image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length42
Median length10
Mean length10.001135
Min length1

Characters and Unicode

Total characters678517
Distinct characters31
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)0.1%

Sample

1st row17/09/2021
2nd row06/11/2021
3rd row28/12/2021
4th row26/11/2021
5th row12/01/2022
ValueCountFrequency (%)
27/10/2021 609
 
0.9%
26/10/2021 566
 
0.8%
04/11/2021 555
 
0.8%
20/10/2021 542
 
0.8%
28/10/2021 538
 
0.8%
21/12/2021 533
 
0.8%
19/11/2021 530
 
0.8%
18/11/2021 528
 
0.8%
05/11/2021 526
 
0.8%
09/11/2021 524
 
0.8%
Other values (636) 62408
92.0%
2023-09-22T21:42:36.100147image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 212349
31.3%
0 142929
21.1%
/ 135682
20.0%
1 110025
16.2%
3 17730
 
2.6%
4 12721
 
1.9%
9 11412
 
1.7%
5 9464
 
1.4%
6 9344
 
1.4%
7 8559
 
1.3%
Other values (21) 8302
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 542733
80.0%
Other Punctuation 135682
 
20.0%
Uppercase Letter 78
 
< 0.1%
Space Separator 15
 
< 0.1%
Dash Punctuation 9
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 11
14.1%
C 10
12.8%
O 10
12.8%
N 9
11.5%
V 7
9.0%
I 7
9.0%
T 5
6.4%
R 4
 
5.1%
D 3
 
3.8%
S 2
 
2.6%
Other values (8) 10
12.8%
Decimal Number
ValueCountFrequency (%)
2 212349
39.1%
0 142929
26.3%
1 110025
20.3%
3 17730
 
3.3%
4 12721
 
2.3%
9 11412
 
2.1%
5 9464
 
1.7%
6 9344
 
1.7%
7 8559
 
1.6%
8 8200
 
1.5%
Other Punctuation
ValueCountFrequency (%)
/ 135682
100.0%
Space Separator
ValueCountFrequency (%)
15
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 678439
> 99.9%
Latin 78
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 11
14.1%
C 10
12.8%
O 10
12.8%
N 9
11.5%
V 7
9.0%
I 7
9.0%
T 5
6.4%
R 4
 
5.1%
D 3
 
3.8%
S 2
 
2.6%
Other values (8) 10
12.8%
Common
ValueCountFrequency (%)
2 212349
31.3%
0 142929
21.1%
/ 135682
20.0%
1 110025
16.2%
3 17730
 
2.6%
4 12721
 
1.9%
9 11412
 
1.7%
5 9464
 
1.4%
6 9344
 
1.4%
7 8559
 
1.3%
Other values (3) 8224
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 678517
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 212349
31.3%
0 142929
21.1%
/ 135682
20.0%
1 110025
16.2%
3 17730
 
2.6%
4 12721
 
1.9%
9 11412
 
1.7%
5 9464
 
1.4%
6 9344
 
1.4%
7 8559
 
1.3%
Other values (21) 8302
 
1.2%

FAB_COV_1
Text

MISSING 

Distinct159
Distinct (%)0.1%
Missing123297
Missing (%)52.3%
Memory size14.4 MiB
2023-09-22T21:42:36.335951image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length60
Median length51
Mean length42.307861
Min length2

Characters and Unicode

Total characters4754769
Distinct characters42
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique79 ?
Unique (%)0.1%

Sample

1st row86 - COVID-19 SINOVAC/BUTANTAN - CORONAVAC
2nd row85 - COVID-19 ASTRAZENECA/FIOCRUZ - COVISHIELD
3rd row86 - COVID-19 SINOVAC/BUTANTAN - CORONAVAC
4th row85 - COVID-19 ASTRAZENECA/FIOCRUZ - COVISHIELD
5th row86 - COVID-19 SINOVAC/BUTANTAN - CORONAVAC
ValueCountFrequency (%)
221971
31.7%
covid-19 110995
15.9%
coronavac 49524
 
7.1%
sinovac/butantan 48806
 
7.0%
86 48780
 
7.0%
astrazeneca/fiocruz 34038
 
4.9%
covishield 34028
 
4.9%
85 34026
 
4.9%
pfizer 26523
 
3.8%
comirnaty 26238
 
3.7%
Other values (151) 65043
 
9.3%
2023-09-22T21:42:36.790880image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
587588
12.4%
A 410196
 
8.6%
C 402904
 
8.5%
O 365968
 
7.7%
I 339108
 
7.1%
- 334431
 
7.0%
N 269610
 
5.7%
V 244080
 
5.1%
R 189205
 
4.0%
T 171914
 
3.6%
Other values (32) 1439765
30.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 3293573
69.3%
Space Separator 587588
 
12.4%
Decimal Number 456054
 
9.6%
Dash Punctuation 334431
 
7.0%
Other Punctuation 83102
 
1.7%
Open Punctuation 10
 
< 0.1%
Close Punctuation 10
 
< 0.1%
Other Letter 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 410196
12.5%
C 402904
12.2%
O 365968
11.1%
I 339108
10.3%
N 269610
8.2%
V 244080
7.4%
R 189205
 
5.7%
T 171914
 
5.2%
D 163530
 
5.0%
E 154123
 
4.7%
Other values (14) 582935
17.7%
Decimal Number
ValueCountFrequency (%)
9 125978
27.6%
1 117617
25.8%
8 99316
21.8%
6 48868
 
10.7%
5 39201
 
8.6%
7 14500
 
3.2%
2 5345
 
1.2%
0 5201
 
1.1%
3 22
 
< 0.1%
4 6
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
/ 82937
99.8%
. 162
 
0.2%
, 3
 
< 0.1%
Space Separator
ValueCountFrequency (%)
587588
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 334431
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Other Letter
ValueCountFrequency (%)
ª 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3293574
69.3%
Common 1461195
30.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 410196
12.5%
C 402904
12.2%
O 365968
11.1%
I 339108
10.3%
N 269610
8.2%
V 244080
7.4%
R 189205
 
5.7%
T 171914
 
5.2%
D 163530
 
5.0%
E 154123
 
4.7%
Other values (15) 582936
17.7%
Common
ValueCountFrequency (%)
587588
40.2%
- 334431
22.9%
9 125978
 
8.6%
1 117617
 
8.0%
8 99316
 
6.8%
/ 82937
 
5.7%
6 48868
 
3.3%
5 39201
 
2.7%
7 14500
 
1.0%
2 5345
 
0.4%
Other values (7) 5414
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4754768
> 99.9%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
587588
12.4%
A 410196
 
8.6%
C 402904
 
8.5%
O 365968
 
7.7%
I 339108
 
7.1%
- 334431
 
7.0%
N 269610
 
5.7%
V 244080
 
5.1%
R 189205
 
4.0%
T 171914
 
3.6%
Other values (31) 1439764
30.3%
None
ValueCountFrequency (%)
ª 1
100.0%

FAB_COV_2
Text

MISSING 

Distinct139
Distinct (%)0.1%
Missing133798
Missing (%)56.8%
Memory size13.7 MiB
2023-09-22T21:42:37.012612image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length60
Median length46
Mean length42.133858
Min length2

Characters and Unicode

Total characters4292766
Distinct characters42
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique62 ?
Unique (%)0.1%

Sample

1st row86 - COVID-19 SINOVAC/BUTANTAN - CORONAVAC
2nd row86 - COVID-19 SINOVAC/BUTANTAN - CORONAVAC
3rd row85 - COVID-19 ASTRAZENECA/FIOCRUZ - COVISHIELD
4th row86 - COVID-19 SINOVAC/BUTANTAN - CORONAVAC
5th rowASTRAZENECA
ValueCountFrequency (%)
201384
32.3%
covid-19 100696
16.2%
coronavac 49194
 
7.9%
sinovac/butantan 48644
 
7.8%
86 48618
 
7.8%
astrazeneca/fiocruz 31245
 
5.0%
covishield 31238
 
5.0%
85 31236
 
5.0%
pfizer 18515
 
3.0%
comirnaty 18300
 
2.9%
Other values (132) 43888
 
7.0%
2023-09-22T21:42:37.457532image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
521075
12.1%
A 383992
 
8.9%
C 372389
 
8.7%
O 336575
 
7.8%
- 304329
 
7.1%
I 295327
 
6.9%
N 253111
 
5.9%
V 230252
 
5.4%
R 161039
 
3.8%
T 157163
 
3.7%
Other values (32) 1277514
29.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 2977167
69.4%
Space Separator 521075
 
12.1%
Decimal Number 410156
 
9.6%
Dash Punctuation 304329
 
7.1%
Other Punctuation 80020
 
1.9%
Open Punctuation 9
 
< 0.1%
Close Punctuation 9
 
< 0.1%
Other Letter 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 383992
12.9%
C 372389
12.5%
O 336575
11.3%
I 295327
9.9%
N 253111
8.5%
V 230252
7.7%
R 161039
 
5.4%
T 157163
 
5.3%
D 144117
 
4.8%
E 129457
 
4.3%
Other values (14) 513745
17.3%
Decimal Number
ValueCountFrequency (%)
9 112842
27.5%
1 105458
25.7%
8 93364
22.8%
6 48635
11.9%
5 33761
 
8.2%
7 10972
 
2.7%
2 2560
 
0.6%
0 2544
 
0.6%
3 16
 
< 0.1%
4 4
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
/ 79994
> 99.9%
. 25
 
< 0.1%
, 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
521075
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 304329
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Other Letter
ValueCountFrequency (%)
ª 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2977168
69.4%
Common 1315598
30.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 383992
12.9%
C 372389
12.5%
O 336575
11.3%
I 295327
9.9%
N 253111
8.5%
V 230252
7.7%
R 161039
 
5.4%
T 157163
 
5.3%
D 144117
 
4.8%
E 129457
 
4.3%
Other values (15) 513746
17.3%
Common
ValueCountFrequency (%)
521075
39.6%
- 304329
23.1%
9 112842
 
8.6%
1 105458
 
8.0%
8 93364
 
7.1%
/ 79994
 
6.1%
6 48635
 
3.7%
5 33761
 
2.6%
7 10972
 
0.8%
2 2560
 
0.2%
Other values (7) 2608
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4292765
> 99.9%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
521075
12.1%
A 383992
 
8.9%
C 372389
 
8.7%
O 336575
 
7.8%
- 304329
 
7.1%
I 295327
 
6.9%
N 253111
 
5.9%
V 230252
 
5.4%
R 161039
 
3.8%
T 157163
 
3.7%
Other values (31) 1277513
29.8%
None
ValueCountFrequency (%)
ª 1
100.0%

FAB_COVREF
Text

MISSING 

Distinct84
Distinct (%)0.1%
Missing167965
Missing (%)71.3%
Memory size11.0 MiB
2023-09-22T21:42:37.669327image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length60
Median length32
Mean length34.391512
Min length1

Characters and Unicode

Total characters2328890
Distinct characters43
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)0.1%

Sample

1st row87 - COVID-19 PFIZER - COMIRNATY
2nd row87 - COVID-19 PFIZER - COMIRNATY
3rd row87 - COVID-19 PFIZER - COMIRNATY
4th row87 - COVID-19 PFIZER - COMIRNATY
5th rowPFIZER
ValueCountFrequency (%)
133897
33.1%
covid-19 66945
16.6%
pfizer 48381
 
12.0%
comirnaty 47840
 
11.8%
87 46055
 
11.4%
janssen 8049
 
2.0%
ad26.cov2.s 8009
 
2.0%
88 8008
 
2.0%
astrazeneca/fiocruz 6533
 
1.6%
covishield 6532
 
1.6%
Other values (90) 24124
 
6.0%
2023-09-22T21:42:38.108577image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
336656
14.5%
- 200938
 
8.6%
I 189683
 
8.1%
C 156738
 
6.7%
O 149668
 
6.4%
R 114492
 
4.9%
A 108800
 
4.7%
V 91968
 
3.9%
N 90092
 
3.9%
D 82018
 
3.5%
Other values (33) 807837
34.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1470905
63.2%
Space Separator 336656
 
14.5%
Decimal Number 293300
 
12.6%
Dash Punctuation 200938
 
8.6%
Other Punctuation 27059
 
1.2%
Open Punctuation 16
 
< 0.1%
Close Punctuation 16
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
I 189683
12.9%
C 156738
10.7%
O 149668
10.2%
R 114492
 
7.8%
A 108800
 
7.4%
V 91968
 
6.3%
N 90092
 
6.1%
D 82018
 
5.6%
E 79442
 
5.4%
T 65279
 
4.4%
Other values (15) 342725
23.3%
Decimal Number
ValueCountFrequency (%)
8 73173
24.9%
1 68375
23.3%
9 67915
23.2%
7 46059
15.7%
2 16044
 
5.5%
6 12488
 
4.3%
5 6539
 
2.2%
0 1359
 
0.5%
3 1345
 
0.5%
4 3
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 16020
59.2%
/ 11025
40.7%
, 11
 
< 0.1%
¿ 3
 
< 0.1%
Space Separator
ValueCountFrequency (%)
336656
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 200938
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1470905
63.2%
Common 857985
36.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
I 189683
12.9%
C 156738
10.7%
O 149668
10.2%
R 114492
 
7.8%
A 108800
 
7.4%
V 91968
 
6.3%
N 90092
 
6.1%
D 82018
 
5.6%
E 79442
 
5.4%
T 65279
 
4.4%
Other values (15) 342725
23.3%
Common
ValueCountFrequency (%)
336656
39.2%
- 200938
23.4%
8 73173
 
8.5%
1 68375
 
8.0%
9 67915
 
7.9%
7 46059
 
5.4%
2 16044
 
1.9%
. 16020
 
1.9%
6 12488
 
1.5%
/ 11025
 
1.3%
Other values (8) 9292
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2328887
> 99.9%
None 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
336656
14.5%
- 200938
 
8.6%
I 189683
 
8.1%
C 156738
 
6.7%
O 149668
 
6.4%
R 114492
 
4.9%
A 108800
 
4.7%
V 91968
 
3.9%
N 90092
 
3.9%
D 82018
 
3.5%
Other values (32) 807834
34.7%
None
ValueCountFrequency (%)
¿ 3
100.0%

LAB_PR_COV
Text

MISSING 

Distinct162
Distinct (%)0.1%
Missing123298
Missing (%)52.3%
Memory size14.4 MiB
2023-09-22T21:42:38.343405image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length60
Median length51
Mean length42.30717
Min length2

Characters and Unicode

Total characters4754649
Distinct characters42
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique82 ?
Unique (%)0.1%

Sample

1st row86 - COVID-19 SINOVAC/BUTANTAN - CORONAVAC
2nd row85 - COVID-19 ASTRAZENECA/FIOCRUZ - COVISHIELD
3rd row86 - COVID-19 SINOVAC/BUTANTAN - CORONAVAC
4th row85 - COVID-19 ASTRAZENECA/FIOCRUZ - COVISHIELD
5th row86 - COVID-19 SINOVAC/BUTANTAN - CORONAVAC
ValueCountFrequency (%)
221963
31.7%
covid-19 110991
15.9%
coronavac 49523
 
7.1%
sinovac/butantan 48805
 
7.0%
86 48779
 
7.0%
astrazeneca/fiocruz 34038
 
4.9%
covishield 34028
 
4.9%
85 34026
 
4.9%
pfizer 26520
 
3.8%
comirnaty 26235
 
3.7%
Other values (154) 65043
 
9.3%
2023-09-22T21:42:38.797608image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
587568
12.4%
A 410188
 
8.6%
C 402894
 
8.5%
O 365958
 
7.7%
I 339097
 
7.1%
- 334419
 
7.0%
N 269603
 
5.7%
V 244074
 
5.1%
R 189198
 
4.0%
T 171909
 
3.6%
Other values (32) 1439741
30.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 3293486
69.3%
Space Separator 587568
 
12.4%
Decimal Number 456054
 
9.6%
Dash Punctuation 334419
 
7.0%
Other Punctuation 83101
 
1.7%
Open Punctuation 10
 
< 0.1%
Close Punctuation 10
 
< 0.1%
Other Letter 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 410188
12.5%
C 402894
12.2%
O 365958
11.1%
I 339097
10.3%
N 269603
8.2%
V 244074
7.4%
R 189198
 
5.7%
T 171909
 
5.2%
D 163526
 
5.0%
E 154120
 
4.7%
Other values (14) 582919
17.7%
Decimal Number
ValueCountFrequency (%)
9 125975
27.6%
1 117618
25.8%
8 99314
21.8%
6 48867
 
10.7%
5 39201
 
8.6%
7 14498
 
3.2%
2 5347
 
1.2%
0 5204
 
1.1%
3 23
 
< 0.1%
4 7
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
/ 82936
99.8%
. 162
 
0.2%
, 3
 
< 0.1%
Space Separator
ValueCountFrequency (%)
587568
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 334419
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Other Letter
ValueCountFrequency (%)
ª 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3293487
69.3%
Common 1461162
30.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 410188
12.5%
C 402894
12.2%
O 365958
11.1%
I 339097
10.3%
N 269603
8.2%
V 244074
7.4%
R 189198
 
5.7%
T 171909
 
5.2%
D 163526
 
5.0%
E 154120
 
4.7%
Other values (15) 582920
17.7%
Common
ValueCountFrequency (%)
587568
40.2%
- 334419
22.9%
9 125975
 
8.6%
1 117618
 
8.0%
8 99314
 
6.8%
/ 82936
 
5.7%
6 48867
 
3.3%
5 39201
 
2.7%
7 14498
 
1.0%
2 5347
 
0.4%
Other values (7) 5419
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4754648
> 99.9%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
587568
12.4%
A 410188
 
8.6%
C 402894
 
8.5%
O 365958
 
7.7%
I 339097
 
7.1%
- 334419
 
7.0%
N 269603
 
5.7%
V 244074
 
5.1%
R 189198
 
4.0%
T 171909
 
3.6%
Other values (31) 1439740
30.3%
None
ValueCountFrequency (%)
ª 1
100.0%

LOTE_1_COV
Text

MISSING 

Distinct1419
Distinct (%)1.3%
Missing123693
Missing (%)52.5%
Memory size10.7 MiB
2023-09-22T21:42:39.124861image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length17
Median length6
Mean length7.32413
Min length1

Characters and Unicode

Total characters820222
Distinct characters72
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique383 ?
Unique (%)0.3%

Sample

1st row202010031
2nd row213VCD025W
3rd row210061
4th rowABX0529
5th row210061
ValueCountFrequency (%)
gc9016 4419
 
3.9%
4120z005 3172
 
2.8%
fp8290 2975
 
2.7%
ff8842 2948
 
2.6%
4120z026 2769
 
2.5%
4120z001 2104
 
1.9%
fp1176 1136
 
1.0%
210009 988
 
0.9%
4120z027 976
 
0.9%
210069 859
 
0.8%
Other values (1241) 89672
80.1%
2023-09-22T21:42:39.665388image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 172543
21.0%
2 131889
16.1%
1 121694
14.8%
4 45745
 
5.6%
5 33383
 
4.1%
3 31075
 
3.8%
9 30514
 
3.7%
8 29392
 
3.6%
C 29156
 
3.6%
6 27006
 
3.3%
Other values (62) 167825
20.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 646424
78.8%
Uppercase Letter 171460
 
20.9%
Lowercase Letter 1207
 
0.1%
Space Separator 766
 
0.1%
Other Punctuation 342
 
< 0.1%
Currency Symbol 17
 
< 0.1%
Dash Punctuation 6
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 29156
17.0%
D 26314
15.3%
V 25857
15.1%
F 22020
12.8%
Z 18282
10.7%
W 15525
9.1%
A 8387
 
4.9%
G 5457
 
3.2%
P 5062
 
3.0%
B 3859
 
2.3%
Other values (15) 11541
 
6.7%
Lowercase Letter
ValueCountFrequency (%)
c 232
19.2%
f 147
12.2%
v 146
12.1%
d 140
11.6%
z 94
7.8%
g 89
 
7.4%
w 79
 
6.5%
a 70
 
5.8%
p 44
 
3.6%
b 32
 
2.7%
Other values (15) 134
11.1%
Decimal Number
ValueCountFrequency (%)
0 172543
26.7%
2 131889
20.4%
1 121694
18.8%
4 45745
 
7.1%
5 33383
 
5.2%
3 31075
 
4.8%
9 30514
 
4.7%
8 29392
 
4.5%
6 27006
 
4.2%
7 23183
 
3.6%
Other Punctuation
ValueCountFrequency (%)
. 247
72.2%
* 46
 
13.5%
# 35
 
10.2%
/ 6
 
1.8%
& 5
 
1.5%
% 1
 
0.3%
' 1
 
0.3%
: 1
 
0.3%
Space Separator
ValueCountFrequency (%)
  737
96.2%
29
 
3.8%
Currency Symbol
ValueCountFrequency (%)
$ 17
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 647555
78.9%
Latin 172667
 
21.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
C 29156
16.9%
D 26314
15.2%
V 25857
15.0%
F 22020
12.8%
Z 18282
10.6%
W 15525
9.0%
A 8387
 
4.9%
G 5457
 
3.2%
P 5062
 
2.9%
B 3859
 
2.2%
Other values (40) 12748
7.4%
Common
ValueCountFrequency (%)
0 172543
26.6%
2 131889
20.4%
1 121694
18.8%
4 45745
 
7.1%
5 33383
 
5.2%
3 31075
 
4.8%
9 30514
 
4.7%
8 29392
 
4.5%
6 27006
 
4.2%
7 23183
 
3.6%
Other values (12) 1131
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 819485
99.9%
None 737
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 172543
21.1%
2 131889
16.1%
1 121694
14.9%
4 45745
 
5.6%
5 33383
 
4.1%
3 31075
 
3.8%
9 30514
 
3.7%
8 29392
 
3.6%
C 29156
 
3.6%
6 27006
 
3.3%
Other values (61) 167088
20.4%
None
ValueCountFrequency (%)
  737
100.0%

LOTE_2_COV
Text

MISSING 

Distinct1423
Distinct (%)1.4%
Missing134130
Missing (%)56.9%
Memory size10.3 MiB
2023-09-22T21:42:40.007319image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length14
Median length6
Mean length7.3891504
Min length1

Characters and Unicode

Total characters750383
Distinct characters70
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique332 ?
Unique (%)0.3%

Sample

1st row202010031
2nd row210137
3rd row216VCD216Z
4th row210144
5th row215VCD163Z
ValueCountFrequency (%)
210223 3371
 
3.3%
gc9016 1930
 
1.9%
210130 1168
 
1.1%
fr8392 1066
 
1.0%
fp0362 1029
 
1.0%
fp8290 831
 
0.8%
210046 792
 
0.8%
abx0529 747
 
0.7%
210048 689
 
0.7%
fn4073 683
 
0.7%
Other values (1230) 89285
87.9%
2023-09-22T21:42:40.563914image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 135773
18.1%
1 131845
17.6%
0 110647
14.7%
3 36949
 
4.9%
4 33399
 
4.5%
C 31941
 
4.3%
D 31745
 
4.2%
V 30584
 
4.1%
5 29029
 
3.9%
8 28225
 
3.8%
Other values (60) 150246
20.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 580266
77.3%
Uppercase Letter 168641
 
22.5%
Lowercase Letter 1293
 
0.2%
Other Punctuation 118
 
< 0.1%
Space Separator 56
 
< 0.1%
Currency Symbol 5
 
< 0.1%
Dash Punctuation 4
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 31941
18.9%
D 31745
18.8%
V 30584
18.1%
F 17119
10.2%
W 16112
9.6%
Z 13984
8.3%
A 6410
 
3.8%
B 4883
 
2.9%
G 4128
 
2.4%
P 2349
 
1.4%
Other values (15) 9386
 
5.6%
Lowercase Letter
ValueCountFrequency (%)
c 256
19.8%
v 213
16.5%
d 211
16.3%
w 140
10.8%
f 124
9.6%
z 82
 
6.3%
g 59
 
4.6%
a 33
 
2.6%
b 31
 
2.4%
p 24
 
1.9%
Other values (15) 120
9.3%
Decimal Number
ValueCountFrequency (%)
2 135773
23.4%
1 131845
22.7%
0 110647
19.1%
3 36949
 
6.4%
4 33399
 
5.8%
5 29029
 
5.0%
8 28225
 
4.9%
6 26285
 
4.5%
9 24696
 
4.3%
7 23418
 
4.0%
Other Punctuation
ValueCountFrequency (%)
. 48
40.7%
# 41
34.7%
* 22
18.6%
& 3
 
2.5%
/ 3
 
2.5%
: 1
 
0.8%
Space Separator
ValueCountFrequency (%)
39
69.6%
  17
30.4%
Currency Symbol
ValueCountFrequency (%)
$ 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 580449
77.4%
Latin 169934
 
22.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
C 31941
18.8%
D 31745
18.7%
V 30584
18.0%
F 17119
10.1%
W 16112
9.5%
Z 13984
8.2%
A 6410
 
3.8%
B 4883
 
2.9%
G 4128
 
2.4%
P 2349
 
1.4%
Other values (40) 10679
 
6.3%
Common
ValueCountFrequency (%)
2 135773
23.4%
1 131845
22.7%
0 110647
19.1%
3 36949
 
6.4%
4 33399
 
5.8%
5 29029
 
5.0%
8 28225
 
4.9%
6 26285
 
4.5%
9 24696
 
4.3%
7 23418
 
4.0%
Other values (10) 183
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 750366
> 99.9%
None 17
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 135773
18.1%
1 131845
17.6%
0 110647
14.7%
3 36949
 
4.9%
4 33399
 
4.5%
C 31941
 
4.3%
D 31745
 
4.2%
V 30584
 
4.1%
5 29029
 
3.9%
8 28225
 
3.8%
Other values (59) 150229
20.0%
None
ValueCountFrequency (%)
  17
100.0%

LOTE_REF
Text

MISSING 

Distinct888
Distinct (%)1.3%
Missing168192
Missing (%)71.4%
Memory size9.2 MiB
2023-09-22T21:42:40.918869image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length17
Median length6
Mean length6.6340495
Min length1

Characters and Unicode

Total characters447732
Distinct characters63
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique218 ?
Unique (%)0.3%

Sample

1st row28235BD
2nd rowFH8023
3rd rowFK8917
4th rowFH8026
5th rowFM2953
ValueCountFrequency (%)
fk8917 1845
 
2.7%
202h21a 1678
 
2.5%
fm3355 1457
 
2.2%
fj2594 1412
 
2.1%
fm3884 1347
 
2.0%
ff2592 1294
 
1.9%
31065bd 1188
 
1.8%
fg3531 1173
 
1.7%
ff5108 1170
 
1.7%
fl4222 1094
 
1.6%
Other values (725) 53845
79.8%
2023-09-22T21:42:41.510143image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 58798
13.1%
F 50374
11.3%
1 40781
 
9.1%
0 35795
 
8.0%
3 35353
 
7.9%
5 31734
 
7.1%
8 27992
 
6.3%
9 23523
 
5.3%
4 23500
 
5.2%
7 16579
 
3.7%
Other values (53) 103303
23.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 306216
68.4%
Uppercase Letter 140219
31.3%
Lowercase Letter 1119
 
0.2%
Other Punctuation 156
 
< 0.1%
Space Separator 13
 
< 0.1%
Dash Punctuation 9
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
F 50374
35.9%
D 10440
 
7.4%
M 9827
 
7.0%
A 8574
 
6.1%
G 8475
 
6.0%
H 7622
 
5.4%
C 6880
 
4.9%
V 6807
 
4.9%
J 5185
 
3.7%
L 4759
 
3.4%
Other values (15) 21276
15.2%
Lowercase Letter
ValueCountFrequency (%)
f 338
30.2%
d 199
17.8%
j 65
 
5.8%
g 64
 
5.7%
v 63
 
5.6%
c 62
 
5.5%
l 53
 
4.7%
m 50
 
4.5%
a 35
 
3.1%
w 30
 
2.7%
Other values (12) 160
14.3%
Decimal Number
ValueCountFrequency (%)
2 58798
19.2%
1 40781
13.3%
0 35795
11.7%
3 35353
11.5%
5 31734
10.4%
8 27992
9.1%
9 23523
7.7%
4 23500
 
7.7%
7 16579
 
5.4%
6 12161
 
4.0%
Other Punctuation
ValueCountFrequency (%)
. 117
75.0%
# 27
 
17.3%
* 8
 
5.1%
/ 4
 
2.6%
Space Separator
ValueCountFrequency (%)
13
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 306394
68.4%
Latin 141338
31.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
F 50374
35.6%
D 10440
 
7.4%
M 9827
 
7.0%
A 8574
 
6.1%
G 8475
 
6.0%
H 7622
 
5.4%
C 6880
 
4.9%
V 6807
 
4.8%
J 5185
 
3.7%
L 4759
 
3.4%
Other values (37) 22395
15.8%
Common
ValueCountFrequency (%)
2 58798
19.2%
1 40781
13.3%
0 35795
11.7%
3 35353
11.5%
5 31734
10.4%
8 27992
9.1%
9 23523
7.7%
4 23500
 
7.7%
7 16579
 
5.4%
6 12161
 
4.0%
Other values (6) 178
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 447732
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 58798
13.1%
F 50374
11.3%
1 40781
 
9.1%
0 35795
 
8.0%
3 35353
 
7.9%
5 31734
 
7.1%
8 27992
 
6.3%
9 23523
 
5.3%
4 23500
 
5.2%
7 16579
 
3.7%
Other values (53) 103303
23.1%

FNT_IN_COV
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing25
Missing (%)< 0.1%
Memory size13.0 MiB
2
225351 
1
 
10305
87 - COVID-19 PFIZER - COMIRNATY
 
1

Length

Max length32
Median length1
Mean length1.0001315
Min length1

Characters and Unicode

Total characters235688
Distinct characters22
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 225351
95.6%
1 10305
 
4.4%
87 - COVID-19 PFIZER - COMIRNATY 1
 
< 0.1%
(Missing) 25
 
< 0.1%

Length

2023-09-22T21:42:41.914696image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:42.264519image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
2 225351
95.6%
1 10305
 
4.4%
2
 
< 0.1%
87 1
 
< 0.1%
covid-19 1
 
< 0.1%
pfizer 1
 
< 0.1%
comirnaty 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
2 225351
95.6%
1 10306
 
4.4%
5
 
< 0.1%
- 3
 
< 0.1%
I 3
 
< 0.1%
C 2
 
< 0.1%
O 2
 
< 0.1%
R 2
 
< 0.1%
Z 1
 
< 0.1%
T 1
 
< 0.1%
Other values (12) 12
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 235660
> 99.9%
Uppercase Letter 20
 
< 0.1%
Space Separator 5
 
< 0.1%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
I 3
15.0%
C 2
 
10.0%
O 2
 
10.0%
R 2
 
10.0%
Z 1
 
5.0%
T 1
 
5.0%
A 1
 
5.0%
N 1
 
5.0%
M 1
 
5.0%
E 1
 
5.0%
Other values (5) 5
25.0%
Decimal Number
ValueCountFrequency (%)
2 225351
95.6%
1 10306
 
4.4%
9 1
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 235668
> 99.9%
Latin 20
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
I 3
15.0%
C 2
 
10.0%
O 2
 
10.0%
R 2
 
10.0%
Z 1
 
5.0%
T 1
 
5.0%
A 1
 
5.0%
N 1
 
5.0%
M 1
 
5.0%
E 1
 
5.0%
Other values (5) 5
25.0%
Common
ValueCountFrequency (%)
2 225351
95.6%
1 10306
 
4.4%
5
 
< 0.1%
- 3
 
< 0.1%
9 1
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 235688
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 225351
95.6%
1 10306
 
4.4%
5
 
< 0.1%
- 3
 
< 0.1%
I 3
 
< 0.1%
C 2
 
< 0.1%
O 2
 
< 0.1%
R 2
 
< 0.1%
Z 1
 
< 0.1%
T 1
 
< 0.1%
Other values (12) 12
 
< 0.1%

DOSE_2REF
Text

MISSING 

Distinct454
Distinct (%)1.2%
Missing197100
Missing (%)83.6%
Memory size8.5 MiB
2023-09-22T21:42:42.687105image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9998963
Min length6

Characters and Unicode

Total characters385816
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)0.2%

Sample

1st row11/04/2022
2nd row10/05/2022
3rd row19/04/2022
4th row25/05/2022
5th row09/06/2022
ValueCountFrequency (%)
05/04/2022 667
 
1.7%
06/04/2022 628
 
1.6%
13/04/2022 618
 
1.6%
19/04/2022 591
 
1.5%
12/04/2022 586
 
1.5%
07/04/2022 578
 
1.5%
08/04/2022 563
 
1.5%
18/04/2022 544
 
1.4%
11/04/2022 543
 
1.4%
04/04/2022 529
 
1.4%
Other values (444) 32735
84.8%
2023-09-22T21:42:43.551021image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 132973
34.5%
0 90863
23.6%
/ 77162
20.0%
1 20580
 
5.3%
4 13581
 
3.5%
6 11301
 
2.9%
5 10655
 
2.8%
3 9992
 
2.6%
7 7748
 
2.0%
8 6242
 
1.6%
Other values (3) 4719
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 308652
80.0%
Other Punctuation 77162
 
20.0%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 132973
43.1%
0 90863
29.4%
1 20580
 
6.7%
4 13581
 
4.4%
6 11301
 
3.7%
5 10655
 
3.5%
3 9992
 
3.2%
7 7748
 
2.5%
8 6242
 
2.0%
9 4717
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
F 1
50.0%
M 1
50.0%
Other Punctuation
ValueCountFrequency (%)
/ 77162
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 385814
> 99.9%
Latin 2
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
2 132973
34.5%
0 90863
23.6%
/ 77162
20.0%
1 20580
 
5.3%
4 13581
 
3.5%
6 11301
 
2.9%
5 10655
 
2.8%
3 9992
 
2.6%
7 7748
 
2.0%
8 6242
 
1.6%
Latin
ValueCountFrequency (%)
F 1
50.0%
M 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 385816
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 132973
34.5%
0 90863
23.6%
/ 77162
20.0%
1 20580
 
5.3%
4 13581
 
3.5%
6 11301
 
2.9%
5 10655
 
2.8%
3 9992
 
2.6%
7 7748
 
2.0%
8 6242
 
1.6%
Other values (3) 4719
 
1.2%

FAB_COVRF2
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct45
Distinct (%)0.1%
Missing197150
Missing (%)83.7%
Memory size11.0 MiB
88 - COVID-19 JANSSEN - AD26.COV2.S
12712 
87 - COVID-19 PFIZER - COMIRNATY
11391 
85 - COVID-19 ASTRAZENECA/FIOCRUZ - COVISHIELD
11356 
86 - COVID-19 SINOVAC/BUTANTAN - CORONAVAC
2602 
103 - COVID-19 PFIZER - COMIRNATY BIVALENTE
 
124
Other values (40)
 
347

Length

Max length46
Median length43
Mean length37.724644
Min length1

Characters and Unicode

Total characters1453606
Distinct characters40
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)< 0.1%

Sample

1st row87 - COVID-19 PFIZER - COMIRNATY
2nd row87 - COVID-19 PFIZER - COMIRNATY
3rd row87 - COVID-19 PFIZER - COMIRNATY
4th row87 - COVID-19 PFIZER - COMIRNATY
5th row88 - COVID-19 JANSSEN - AD26.COV2.S

Common Values

ValueCountFrequency (%)
88 - COVID-19 JANSSEN - AD26.COV2.S 12712
 
5.4%
87 - COVID-19 PFIZER - COMIRNATY 11391
 
4.8%
85 - COVID-19 ASTRAZENECA/FIOCRUZ - COVISHIELD 11356
 
4.8%
86 - COVID-19 SINOVAC/BUTANTAN - CORONAVAC 2602
 
1.1%
103 - COVID-19 PFIZER - COMIRNATY BIVALENTE 124
 
0.1%
89 - COVID-19 ASTRAZENECA - CHADOX1-S 111
 
< 0.1%
JANSSEN 49
 
< 0.1%
PFIZER 48
 
< 0.1%
98 - COVID-19 SINOVAC - CORONAVAC 31
 
< 0.1%
ASTRAZENECA 14
 
< 0.1%
Other values (35) 94
 
< 0.1%
(Missing) 197150
83.7%

Length

2023-09-22T21:42:43.776257image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
76659
33.3%
covid-19 38337
16.6%
janssen 12764
 
5.5%
88 12712
 
5.5%
ad26.cov2.s 12712
 
5.5%
pfizer 11576
 
5.0%
comirnaty 11516
 
5.0%
87 11391
 
4.9%
covishield 11358
 
4.9%
astrazeneca/fiocruz 11357
 
4.9%
Other values (41) 19973
 
8.7%

Most occurring characters

ValueCountFrequency (%)
191825
 
13.2%
- 115119
 
7.9%
C 104865
 
7.2%
I 98340
 
6.8%
O 93366
 
6.4%
A 84900
 
5.8%
V 67840
 
4.7%
S 63863
 
4.4%
D 62536
 
4.3%
N 59199
 
4.1%
Other values (30) 511753
35.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 915553
63.0%
Space Separator 191825
 
13.2%
Decimal Number 191716
 
13.2%
Dash Punctuation 115119
 
7.9%
Other Punctuation 39391
 
2.7%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 104865
11.5%
I 98340
10.7%
O 93366
10.2%
A 84900
9.3%
V 67840
 
7.4%
S 63863
 
7.0%
D 62536
 
6.8%
N 59199
 
6.5%
E 58959
 
6.4%
R 48632
 
5.3%
Other values (14) 173053
18.9%
Decimal Number
ValueCountFrequency (%)
8 50915
26.6%
1 38576
20.1%
9 38482
20.1%
2 25431
13.3%
6 15314
 
8.0%
7 11392
 
5.9%
5 11356
 
5.9%
0 126
 
0.1%
3 124
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 25424
64.5%
/ 13966
35.5%
, 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
191825
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 115119
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 915553
63.0%
Common 538053
37.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
C 104865
11.5%
I 98340
10.7%
O 93366
10.2%
A 84900
9.3%
V 67840
 
7.4%
S 63863
 
7.0%
D 62536
 
6.8%
N 59199
 
6.5%
E 58959
 
6.4%
R 48632
 
5.3%
Other values (14) 173053
18.9%
Common
ValueCountFrequency (%)
191825
35.7%
- 115119
21.4%
8 50915
 
9.5%
1 38576
 
7.2%
9 38482
 
7.2%
2 25431
 
4.7%
. 25424
 
4.7%
6 15314
 
2.8%
/ 13966
 
2.6%
7 11392
 
2.1%
Other values (6) 11609
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1453606
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
191825
 
13.2%
- 115119
 
7.9%
C 104865
 
7.2%
I 98340
 
6.8%
O 93366
 
6.4%
A 84900
 
5.8%
V 67840
 
4.7%
S 63863
 
4.4%
D 62536
 
4.3%
N 59199
 
4.1%
Other values (30) 511753
35.2%

LOTE_REF2
Text

MISSING 

Distinct577
Distinct (%)1.5%
Missing197136
Missing (%)83.6%
Memory size8.4 MiB
2023-09-22T21:42:44.105929image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length20
Median length12
Mean length7.6332434
Min length1

Characters and Unicode

Total characters294231
Distinct characters57
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique160 ?
Unique (%)0.4%

Sample

1st rowFN9606
2nd rowFP7082
3rd rowFN9606
4th rowFM2948
5th row203H21A
ValueCountFrequency (%)
202h21a 1822
 
4.7%
fp7082 1544
 
4.0%
203h21a 1341
 
3.5%
fn9606 1269
 
3.3%
fp8073 1101
 
2.9%
fm2948 971
 
2.5%
207h21a 786
 
2.0%
204j21a 781
 
2.0%
209f21a 713
 
1.8%
210f21a 702
 
1.8%
Other values (494) 27520
71.4%
2023-09-22T21:42:45.844702image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 52587
17.9%
1 36138
12.3%
0 29119
 
9.9%
3 15422
 
5.2%
7 13434
 
4.6%
8 12844
 
4.4%
F 12724
 
4.3%
C 11948
 
4.1%
A 11848
 
4.0%
D 11758
 
4.0%
Other values (47) 86409
29.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 195066
66.3%
Uppercase Letter 98544
33.5%
Lowercase Letter 601
 
0.2%
Other Punctuation 12
 
< 0.1%
Space Separator 4
 
< 0.1%
Currency Symbol 2
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
F 12724
12.9%
C 11948
12.1%
A 11848
12.0%
D 11758
11.9%
V 11691
11.9%
W 6404
6.5%
P 5855
5.9%
O 5238
5.3%
H 4930
 
5.0%
Z 3963
 
4.0%
Other values (12) 12185
12.4%
Lowercase Letter
ValueCountFrequency (%)
v 101
16.8%
c 100
16.6%
d 98
16.3%
w 71
11.8%
f 55
9.2%
o 36
 
6.0%
a 31
 
5.2%
p 30
 
5.0%
z 19
 
3.2%
n 15
 
2.5%
Other values (9) 45
7.5%
Decimal Number
ValueCountFrequency (%)
2 52587
27.0%
1 36138
18.5%
0 29119
14.9%
3 15422
 
7.9%
7 13434
 
6.9%
8 12844
 
6.6%
5 9516
 
4.9%
4 9082
 
4.7%
9 8839
 
4.5%
6 8085
 
4.1%
Other Punctuation
ValueCountFrequency (%)
. 7
58.3%
/ 4
33.3%
# 1
 
8.3%
Space Separator
ValueCountFrequency (%)
4
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 195086
66.3%
Latin 99145
33.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
F 12724
12.8%
C 11948
12.1%
A 11848
12.0%
D 11758
11.9%
V 11691
11.8%
W 6404
6.5%
P 5855
5.9%
O 5238
5.3%
H 4930
 
5.0%
Z 3963
 
4.0%
Other values (31) 12786
12.9%
Common
ValueCountFrequency (%)
2 52587
27.0%
1 36138
18.5%
0 29119
14.9%
3 15422
 
7.9%
7 13434
 
6.9%
8 12844
 
6.6%
5 9516
 
4.9%
4 9082
 
4.7%
9 8839
 
4.5%
6 8085
 
4.1%
Other values (6) 20
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 294231
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 52587
17.9%
1 36138
12.3%
0 29119
 
9.9%
3 15422
 
5.2%
7 13434
 
4.6%
8 12844
 
4.4%
F 12724
 
4.3%
C 11948
 
4.1%
A 11848
 
4.0%
D 11758
 
4.0%
Other values (47) 86409
29.4%

TRAT_COV
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct3
Distinct (%)< 0.1%
Missing61044
Missing (%)25.9%
Memory size12.3 MiB
2.0
145002 
9.0
27312 
1.0
 
2324

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters523914
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2.0
2nd row2.0
3rd row2.0
4th row2.0
5th row2.0

Common Values

ValueCountFrequency (%)
2.0 145002
61.5%
9.0 27312
 
11.6%
1.0 2324
 
1.0%
(Missing) 61044
25.9%

Length

2023-09-22T21:42:46.045263image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:46.232200image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
2.0 145002
83.0%
9.0 27312
 
15.6%
1.0 2324
 
1.3%

Most occurring characters

ValueCountFrequency (%)
. 174638
33.3%
0 174638
33.3%
2 145002
27.7%
9 27312
 
5.2%
1 2324
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 349276
66.7%
Other Punctuation 174638
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 174638
50.0%
2 145002
41.5%
9 27312
 
7.8%
1 2324
 
0.7%
Other Punctuation
ValueCountFrequency (%)
. 174638
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 523914
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 174638
33.3%
0 174638
33.3%
2 145002
27.7%
9 27312
 
5.2%
1 2324
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 523914
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 174638
33.3%
0 174638
33.3%
2 145002
27.7%
9 27312
 
5.2%
1 2324
 
0.4%

TIPO_TRAT
Categorical

HIGH CORRELATION  MISSING 

Distinct3
Distinct (%)0.4%
Missing234997
Missing (%)99.7%
Memory size9.0 MiB
3.0
513 
1.0
128 
2.0
 
44

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters2055
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3.0
2nd row1.0
3rd row3.0
4th row3.0
5th row1.0

Common Values

ValueCountFrequency (%)
3.0 513
 
0.2%
1.0 128
 
0.1%
2.0 44
 
< 0.1%
(Missing) 234997
99.7%

Length

2023-09-22T21:42:46.379639image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-09-22T21:42:46.570326image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
3.0 513
74.9%
1.0 128
 
18.7%
2.0 44
 
6.4%

Most occurring characters

ValueCountFrequency (%)
. 685
33.3%
0 685
33.3%
3 513
25.0%
1 128
 
6.2%
2 44
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1370
66.7%
Other Punctuation 685
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 685
50.0%
3 513
37.4%
1 128
 
9.3%
2 44
 
3.2%
Other Punctuation
ValueCountFrequency (%)
. 685
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2055
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 685
33.3%
0 685
33.3%
3 513
25.0%
1 128
 
6.2%
2 44
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2055
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 685
33.3%
0 685
33.3%
3 513
25.0%
1 128
 
6.2%
2 44
 
2.1%

OUT_TRAT
Text

MISSING 

Distinct130
Distinct (%)33.2%
Missing235291
Missing (%)99.8%
Memory size7.2 MiB
2023-09-22T21:42:46.770176image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length30
Median length29
Mean length13.081841
Min length2

Characters and Unicode

Total characters5115
Distinct characters38
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique90 ?
Unique (%)23.0%

Sample

1st rowREMDESIVIR
2nd rowCEFTRIAXONA
3rd rowAMOX+CLAVU
4th rowCEFTRIAXONA
5th rowREDENSIVIR
ValueCountFrequency (%)
remdesivir 60
 
12.6%
azitromicina 55
 
11.6%
ceftriaxona 50
 
10.5%
rendesivir 29
 
6.1%
rendesevir 19
 
4.0%
tratamento 14
 
2.9%
suporte 13
 
2.7%
remdesevir 12
 
2.5%
e 12
 
2.5%
11
 
2.3%
Other values (118) 201
42.2%
2023-09-22T21:42:47.208797image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
I 758
14.8%
R 558
10.9%
E 533
10.4%
A 510
10.0%
O 339
 
6.6%
N 336
 
6.6%
T 281
 
5.5%
C 263
 
5.1%
M 252
 
4.9%
V 191
 
3.7%
Other values (28) 1094
21.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 4941
96.6%
Space Separator 88
 
1.7%
Other Punctuation 58
 
1.1%
Decimal Number 14
 
0.3%
Math Symbol 11
 
0.2%
Dash Punctuation 3
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
I 758
15.3%
R 558
11.3%
E 533
10.8%
A 510
10.3%
O 339
 
6.9%
N 336
 
6.8%
T 281
 
5.7%
C 263
 
5.3%
M 252
 
5.1%
V 191
 
3.9%
Other values (14) 920
18.6%
Decimal Number
ValueCountFrequency (%)
0 8
57.1%
1 2
 
14.3%
4 1
 
7.1%
7 1
 
7.1%
5 1
 
7.1%
2 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
, 40
69.0%
/ 14
 
24.1%
? 3
 
5.2%
. 1
 
1.7%
Space Separator
ValueCountFrequency (%)
86
97.7%
  2
 
2.3%
Math Symbol
ValueCountFrequency (%)
+ 11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4941
96.6%
Common 174
 
3.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
I 758
15.3%
R 558
11.3%
E 533
10.8%
A 510
10.3%
O 339
 
6.9%
N 336
 
6.8%
T 281
 
5.7%
C 263
 
5.3%
M 252
 
5.1%
V 191
 
3.9%
Other values (14) 920
18.6%
Common
ValueCountFrequency (%)
86
49.4%
, 40
23.0%
/ 14
 
8.0%
+ 11
 
6.3%
0 8
 
4.6%
- 3
 
1.7%
? 3
 
1.7%
  2
 
1.1%
1 2
 
1.1%
. 1
 
0.6%
Other values (4) 4
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5113
> 99.9%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
I 758
14.8%
R 558
10.9%
E 533
10.4%
A 510
10.0%
O 339
 
6.6%
N 336
 
6.6%
T 281
 
5.5%
C 263
 
5.1%
M 252
 
4.9%
V 191
 
3.7%
Other values (27) 1092
21.4%
None
ValueCountFrequency (%)
  2
100.0%

DT_TRT_COV
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing235682
Missing (%)100.0%
Memory size1.8 MiB

Interactions

2023-09-22T21:40:12.468606image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-22T21:40:08.601124image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-22T21:40:09.605479image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-22T21:40:10.600176image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-22T21:40:11.549820image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-22T21:40:12.675986image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-22T21:40:08.811769image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-22T21:40:09.811490image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-22T21:40:10.804569image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-22T21:40:11.728554image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-22T21:40:13.096665image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-22T21:40:09.019836image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-22T21:40:10.019717image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-22T21:40:11.017720image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-22T21:40:11.904291image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-22T21:40:13.258060image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-22T21:40:09.202836image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-22T21:40:10.205669image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-22T21:40:11.179115image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-22T21:40:12.082027image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-22T21:40:13.457766image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-22T21:40:09.389132image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-22T21:40:10.389529image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-22T21:40:11.360157image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-22T21:40:12.253838image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Correlations

2023-09-22T21:42:47.556692image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
SEM_NOTSEM_PRICO_MUN_RESPNEUMOPATIRES_ANSG_UF_NOTCS_SEXOTP_IDADECS_GESTANTCS_RACACS_ESCOL_NID_PAISCO_PAISSG_UFCS_ZONASURTO_SGNOSOCOMIALAVE_SUINOFEBRETOSSEGARGANTADISPNEIADESC_RESPSATURACAODIARREIAVOMITOOUTRO_SINPUERPERAFATOR_RISCCARDIOPATIHEMATOLOGISIND_DOWNHEPATICAASMADIABETESNEUROLOGICIMUNODEPRERENALOBESIDADEOUT_MORBIVACINAMAE_VACM_AMAMENTAANTIVIRALTP_ANTIVIRHOSPITALSG_UF_INTEUTISUPORT_VENRAIOX_RESAMOSTRATP_AMOSTRAPCR_RESULPOS_PCRFLUTP_FLU_PCRPCR_FLUASUPCR_FLUBLIPOS_PCROUTPCR_VSRPCR_PARA1PCR_PARA2PCR_PARA3PCR_PARA4PCR_ADENOPCR_METAPPCR_BOCAPCR_RINOPCR_OUTROCLASSI_FINCRITERIOEVOLUCAOHISTO_VGMPAIS_VGMPCR_SARS2DOR_ABDFADIGAPERD_OLFTPERD_PALATOMO_RESTP_TES_ANPOS_AN_FLUTP_FLU_ANPOS_AN_OUTAN_SARS2AN_VSRAN_PARA1AN_PARA3AN_ADENOTP_AM_SORTP_SORRES_IGGRES_IGMRES_IGAESTRANGVACINA_COVFNT_IN_COVFAB_COVRF2TRAT_COVTIPO_TRAT
SEM_NOT1.0000.987-0.032-0.0140.1080.0810.0020.0520.0220.0260.0400.0000.0000.0800.0351.0000.0220.0200.0370.0650.0270.0240.0350.0170.0170.0110.0130.0070.0360.0280.0100.0140.0110.0460.0220.0120.0180.0170.0140.0090.0410.0250.0190.0430.0390.0130.0810.0170.0180.0320.0190.0120.0750.1180.1240.0780.0560.0870.0100.0000.1100.0850.0880.0370.0320.1350.0000.0230.1020.0410.0290.0001.0000.0000.0150.0220.0250.0290.0320.0290.1800.2550.1790.0160.0600.0000.0000.0940.0710.1030.0630.0690.0600.0050.0380.0210.0340.0520.092
SEM_PRI0.9871.000-0.028-0.0110.1100.0800.0000.0520.0230.0260.0410.0020.0020.0790.0360.0000.0240.0200.0350.0650.0240.0250.0370.0170.0170.0100.0140.0070.0380.0290.0080.0130.0110.0490.0220.0110.0170.0180.0150.0120.0430.0260.0170.0440.0400.0120.0800.0200.0210.0300.0160.0110.0760.1190.1230.0680.0560.0880.0100.0000.0000.0730.2470.0300.0300.1000.0000.0000.1030.0370.0310.0001.0000.0000.0160.0220.0220.0260.0350.0320.1850.2450.1860.0190.0390.0000.0000.0000.0680.1010.0620.0670.0590.0040.0380.0210.0330.0550.105
CO_MUN_RES-0.032-0.0281.000-0.050-0.0000.8790.3160.2900.2510.2550.3710.5000.5770.9410.3181.0000.0790.1120.4160.0710.1110.0860.0500.1000.0470.0520.0670.0320.0710.0460.0490.0300.0310.0320.0490.0300.0380.0360.3350.4500.5080.1270.4600.4160.4210.3480.9330.2990.5080.1030.5040.3830.1120.0590.0900.1740.1520.0360.0000.4790.4590.4970.3920.4050.5000.5720.5260.7040.3850.3630.4510.0071.0000.0070.0480.0730.0570.0630.0850.0550.1000.1250.0810.0000.0690.0000.3880.0000.3170.5530.2860.2840.2660.5000.4510.0680.1420.0660.075
PNEUMOPATI-0.014-0.011-0.0501.000-0.0260.0140.0000.0000.0000.0001.0000.0000.0000.0140.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.7071.0001.0001.0001.0001.0001.0001.0000.0131.0001.0001.0001.0000.9991.0001.0001.0001.0001.0001.0001.0001.0001.0000.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.4980.0910.0001.0000.0311.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
RES_AN0.1080.110-0.000-0.0261.0000.1920.0090.0490.0500.0640.0750.0040.0040.1900.0560.0000.0670.0470.0730.0510.0650.0770.0650.0480.0370.0330.0480.0320.1330.0730.0460.0410.0380.1070.0840.0470.0470.0470.0320.0700.0620.1090.1270.0700.1000.0620.1890.0670.0730.0700.0840.0180.2460.0720.0220.1120.0770.0431.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.3270.0610.0701.0000.0001.0000.0320.0410.0370.0400.0690.1190.0280.0050.0031.0001.0001.0001.0001.0000.2410.1390.0910.1020.0820.0220.0950.0060.0350.0700.127
SG_UF_NOT0.0810.0800.8790.0140.1921.0000.3540.0490.3370.2730.3140.2140.2440.9790.2181.0000.1330.1910.0970.0940.1460.1170.0710.1080.0670.0690.1090.0500.0780.0680.0580.0430.0590.0720.0610.0480.0700.0560.5810.0770.1360.1710.2200.1370.1170.4111.0000.1050.5180.1380.0900.3890.1600.0850.1120.2390.3300.0500.0690.2340.6970.3440.5080.0000.1470.3080.4200.0560.3970.4260.3870.0061.0000.0240.0670.1050.0710.0920.1220.1270.1920.1590.1300.0540.1210.8910.8880.5060.5890.3500.2280.2520.4110.5030.3850.0670.1430.1780.189
CS_SEXO0.0020.0000.3160.0000.0090.3541.0000.6330.5650.4470.5780.8450.7070.7070.0100.0000.0130.0170.5000.0240.0230.0190.0240.0140.0160.0060.0090.0330.4480.0370.0160.0180.0300.0080.0320.0210.0250.0220.5790.5000.5770.0000.5770.0040.5000.5000.5780.0030.5770.5000.0050.5000.0100.0100.0000.0430.0130.0100.0000.0000.1130.0110.0000.0000.0000.0000.5000.5770.4480.7750.7750.0011.0000.0000.0110.0140.5770.0100.5780.0040.0100.0000.0100.0020.0000.0000.0000.0000.0140.0390.0070.0250.5070.8660.7750.7070.2880.0050.055
TP_IDADE0.0520.0520.2900.0000.0490.0490.6331.0000.5210.4090.5070.7750.6120.5810.0351.0000.0350.0390.5790.0900.1080.0200.0850.0210.0230.5770.0320.0330.7270.5850.5000.5060.0240.0530.0940.0370.0400.0490.0580.0740.0700.6390.6180.5800.5790.5780.4140.0290.0490.5850.5000.0270.5870.1720.5810.5780.5770.5880.0040.3970.7010.0000.0000.7060.5770.5760.5780.8150.1920.7070.7130.0001.0000.0000.0760.0570.5800.0670.5170.0100.1240.0000.0950.0000.0190.0000.0000.0000.1310.5870.5010.4480.0890.7070.8090.7070.2380.0510.000
CS_GESTANT0.0220.0230.2510.0000.0500.3370.5650.5211.0000.0580.3820.4710.4080.3570.0331.0000.0590.0650.5840.0910.0670.0490.0830.0460.0380.0500.0240.0850.1170.1180.0410.0530.0430.0720.0770.0390.0430.0450.5820.0270.0550.0000.5770.5040.5000.5780.4110.0430.5020.0710.0050.3780.0400.0790.0660.0270.0000.0710.0000.0690.6890.0570.2540.5060.5010.5840.7070.5930.3880.4470.4130.0031.0000.0000.0320.0540.0420.0470.0950.0360.0480.0530.0350.0000.0000.0000.0000.3030.1050.5020.3800.3810.3550.5770.5990.0110.0370.0940.084
CS_RACA0.0260.0260.2550.0000.0640.2730.4470.4090.0581.0000.1270.4090.4090.4890.1080.5770.0760.0930.0480.0350.0450.0530.0330.0500.0240.0240.0640.0250.4110.0520.0250.0230.0270.0400.0330.0310.0270.0180.0320.0290.1190.0760.0810.0550.0610.0090.3020.0530.0620.4140.0310.0310.0430.0270.0680.0970.0820.0270.0000.0790.0000.0000.0000.0450.0000.0000.0000.5750.0380.4100.4100.0061.0000.0290.0380.0500.5780.0430.4110.0570.0530.0080.0250.0000.0000.2510.2130.0000.1260.1530.0340.0330.0770.5000.4110.7080.1750.0930.094
CS_ESCOL_N0.0400.0410.3711.0000.0750.3140.5780.5070.3820.1271.0000.6740.6320.5940.0840.0000.0930.1170.1240.1250.0980.0540.1220.5790.0460.5790.0470.0520.4750.5940.5790.5070.0420.1110.1680.0590.0730.0770.5820.5020.1740.5040.1180.5900.5800.7750.5230.7100.5040.1170.6330.3790.4130.1290.5810.3810.4110.5080.0280.5230.0000.0710.4710.7070.0000.0000.7060.1320.4740.4080.4180.000NaN0.0000.0530.0680.0630.0770.1470.0510.1120.1070.0810.0001.0001.0000.1031.0000.3040.1920.0570.0690.4110.5000.5140.0170.0400.1520.024
ID_PAIS0.0000.0020.5000.0000.0040.2140.8450.7750.4710.4090.6741.0001.0001.0000.5001.0000.0120.0230.5780.0210.0110.0190.0190.5770.0140.0000.0110.0270.5000.0270.0220.0190.0170.0000.0310.0190.0200.0030.5780.6320.5770.0000.5770.7070.7070.8170.4480.7070.5000.3780.5000.3780.0000.0000.0000.0000.0000.0080.0000.7010.7010.7050.6860.7060.8160.9990.9131.0000.5350.7070.7560.0001.0001.0000.0040.0080.5770.0230.3780.0000.0000.0000.0080.0000.0001.0001.0001.0000.0170.5770.5000.4480.4540.8690.7560.7080.4070.0001.000
CO_PAIS0.0000.0020.5770.0000.0040.2440.7070.6120.4080.4090.6321.0001.0001.0000.0051.0000.0090.0230.5770.0000.0050.0000.0000.5770.0000.0000.0070.0180.0000.0000.0000.0000.0000.0000.0210.0000.0040.0000.5770.5000.0060.0000.5770.7070.7070.8160.4640.7070.5000.0030.5000.3780.0000.0000.0000.0000.0000.0080.0001.0000.9960.0000.0000.5760.7070.9990.8661.0000.4080.6320.6320.0001.0001.0000.0000.0000.0000.0230.0060.0000.0000.0000.0080.0000.0001.0001.0001.0000.0170.5770.5780.5010.5040.8200.7070.7081.0000.0001.000
SG_UF0.0800.0790.9410.0140.1900.9790.7070.5810.3570.4890.5941.0001.0001.0000.5451.0000.1320.1910.1360.0930.1450.1150.0850.5900.0670.0830.1180.0560.1090.0830.0750.0560.0580.0800.0700.0550.0680.0560.5800.6380.5980.2080.2810.5980.5960.7770.9790.7150.5180.1480.5100.3880.1710.0830.1360.2490.3400.0550.1010.5620.7540.6040.7000.5680.6000.7200.8740.9920.5480.6460.7130.0051.0000.0200.0660.1050.0860.0920.1300.1230.1900.1580.1280.0540.1200.8740.8880.5060.5890.4060.2380.2660.4100.8190.6380.7100.1440.1750.197
CS_ZONA0.0350.0360.3180.0000.0560.2180.0100.0350.0330.1080.0840.5000.0050.5451.0000.7070.0960.1120.0280.0290.0230.0340.0360.0240.0090.0120.0330.0140.0380.0160.0150.0140.0120.0170.0100.0130.0330.0130.0140.5000.5800.0640.0950.0540.0120.0140.4160.0410.0390.0940.0280.0280.0900.0280.0150.0840.0000.0150.0140.5250.1940.5110.8060.5010.5020.5830.5780.5820.5030.0320.5010.0041.0000.0230.0140.0150.0080.0110.0840.0230.0380.0000.0250.0180.0001.0000.2650.2100.1020.0000.0920.0950.0910.0100.0420.0120.0360.0680.093
SURTO_SG1.0000.0001.0001.0000.0001.0000.0001.0001.0000.5770.0001.0001.0001.0000.7071.0000.0001.0001.0000.0000.0000.7070.7070.000NaNNaN1.0000.0001.0001.0001.0001.0001.0001.0001.0001.000NaN1.0001.0001.000NaN0.0000.0000.000NaN1.0001.0000.000NaN1.0001.0001.0000.0000.0000.0000.0000.0000.0000.000NaNNaNNaNNaN1.000NaNNaN1.0001.0001.0001.0001.0000.0000.0000.0000.0001.000NaNNaNNaNNaN0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0001.0001.000NaNNaN0.0000.000
NOSOCOMIAL0.0220.0240.0790.0000.0670.1330.0130.0350.0590.0760.0930.0120.0090.1320.0960.0001.0000.2860.0490.0590.0530.0350.0540.0570.0770.0740.0680.0300.0710.0470.0460.0360.0450.0660.0460.0390.0660.0600.0390.0470.1190.0880.0950.2300.0120.0540.1350.1190.0840.1420.0200.0270.0810.0380.0220.0150.1090.0110.0000.0000.0000.0000.0000.0000.0000.0000.0470.1020.0730.0190.0600.0001.0000.0000.0550.0590.0500.0510.1430.0160.1060.0000.0280.0000.0000.0000.0000.0000.0610.0820.0430.0480.0540.0130.0730.0280.0150.2130.069
AVE_SUINO0.0200.0200.1120.0000.0470.1910.0170.0390.0650.0930.1170.0230.0230.1910.1121.0000.2861.0000.0530.0510.0610.0430.0570.0630.0780.0750.0700.0380.0390.0480.0530.0400.0470.0500.0420.0390.0450.0460.0530.0520.1660.1190.1060.1780.0690.0360.1970.0860.0610.1110.0400.0130.0490.0510.0070.0620.0660.0120.0000.0000.7020.0000.0000.2540.1440.3480.1350.2360.0340.0400.0570.0001.0000.0000.0490.0510.0500.0600.1060.0350.0810.0420.0540.0000.0000.0000.0000.0000.0730.1040.0750.0690.0530.0170.0590.0240.0160.1890.000
FEBRE0.0370.0350.4160.0000.0730.0970.5000.5790.5840.0480.1240.5780.5770.1360.0281.0000.0490.0531.0000.4390.2800.2800.3300.2810.3860.3820.2050.1380.1320.1430.1970.2010.1930.2080.1160.2060.2070.1870.1280.5830.5780.0460.7070.5800.7070.5010.5870.0630.0710.0840.0070.0180.0780.0900.0440.0450.1320.0320.0000.0390.7000.0250.0000.5780.5770.7060.7070.7350.0900.0250.1080.000NaN0.0000.2730.2860.2290.2310.0640.0130.1170.0320.0730.0000.0000.0000.0000.1640.0840.5780.5780.5780.0340.0190.5860.0120.0360.0570.023
TOSSE0.0650.0650.0710.0000.0510.0940.0240.0900.0910.0350.1250.0210.0000.0930.0290.0000.0590.0510.4391.0000.2950.3350.3580.2770.3820.3730.2140.1440.1050.1470.1910.1870.1910.2440.1540.1880.1840.1900.1640.0740.0470.0170.0280.0800.0090.0630.0860.0930.1150.1060.0090.0210.0600.0580.0170.0380.0960.0160.0150.0860.0000.1250.4440.0650.0820.0000.0000.2850.1060.0240.1610.004NaN0.0100.2740.2930.2320.2320.0850.0130.0690.0490.0550.0000.0000.0000.0000.1910.0940.0380.0330.0220.0340.0240.1180.0110.0450.0670.000
GARGANTA0.0270.0240.1110.0000.0650.1460.0230.1080.0670.0450.0980.0110.0050.1450.0230.0000.0530.0610.2800.2951.0000.3080.2710.2530.3550.3520.2320.1780.0370.1780.2380.2280.2440.2440.1950.2210.2460.2390.2050.0980.0780.0620.0370.0390.0360.0610.1340.0610.0920.0810.0170.0120.0510.0730.0330.0520.0510.0460.0000.0000.0940.0000.0000.0220.0290.0780.0190.0700.0850.0140.0450.0001.0000.0000.5190.4240.5070.5030.0510.0000.1070.0720.0840.0000.0000.0000.0000.0000.0820.0480.0460.0780.0480.0120.0790.0070.0180.0380.079
DISPNEIA0.0240.0250.0860.0000.0770.1170.0190.0200.0490.0530.0540.0190.0000.1150.0340.7070.0350.0430.2800.3350.3081.0000.5060.4220.3440.3320.1740.1870.0570.1960.2350.2440.2430.2610.1730.2220.2320.2390.2070.0800.0370.0260.0320.0370.1080.0810.1170.0550.2020.1140.0190.0160.0270.0980.0430.0320.0390.0370.0020.0000.0000.0000.0000.0000.0000.0060.0120.1840.0660.0250.0650.0001.0000.0000.3330.3020.2770.2770.0670.0300.1020.1350.1160.0000.0000.0000.0000.0000.0590.0550.0540.0520.0590.0210.0210.0040.0160.0450.094
DESC_RESP0.0350.0370.0500.0000.0650.0710.0240.0850.0830.0330.1220.0190.0000.0850.0360.7070.0540.0570.3300.3580.2710.5061.0000.7080.4040.3980.2070.2300.0220.2180.2670.2930.2800.2950.1990.2630.2640.2700.2390.5820.0390.0230.0740.0840.1260.0870.0840.0530.2140.1290.0280.0160.0490.1180.0000.0370.0610.0510.0040.0030.1690.0000.0000.0000.0000.0590.0270.3150.0960.0220.0460.0001.0000.0000.2990.3490.2540.2540.0730.0270.1160.0920.1270.0000.0000.0000.0000.0000.1690.0780.0740.0730.0780.0230.0860.0150.0050.0930.000
SATURACAO0.0170.0170.1000.0000.0480.1080.0140.0210.0460.0500.5790.5770.5770.5900.0240.0000.0570.0630.2810.2770.2530.4220.7081.0000.3630.3590.1690.1450.1090.1850.2180.2260.2250.2250.1660.2170.2160.2130.1970.7100.0700.0280.0690.5790.5870.5830.1480.5830.3140.1080.0390.0180.0330.0710.0480.0620.0350.0270.0000.0000.0000.0000.0000.0000.0000.0000.0150.1910.0550.0200.0910.0001.0000.0000.2720.3140.2350.2380.0830.0220.1230.1340.1410.0000.0000.0000.0000.0000.0830.0760.0680.0750.0700.0180.0410.0140.0200.0610.019
DIARREIA0.0170.0170.0470.0000.0370.0670.0160.0230.0380.0240.0460.0140.0000.0670.009NaN0.0770.0780.3860.3820.3550.3440.4040.3631.0000.6370.3070.2540.0170.2410.3270.3230.3390.3250.2530.3100.3360.3270.2660.1230.0610.0340.0420.0700.0200.0610.0660.0550.0580.0590.0150.0100.0240.0920.0220.0180.0710.0160.0000.0000.0000.0000.0000.0000.0000.0000.0000.2840.0270.0180.0410.000NaN0.0000.4510.4390.3530.3530.0770.0080.0670.0000.0830.0000.0000.0000.0000.0000.0900.0330.0360.0360.0370.0170.0320.0150.0190.0800.087
VOMITO0.0110.0100.0520.0000.0330.0690.0060.5770.0500.0240.5790.0000.0000.0830.012NaN0.0740.0750.3820.3730.3520.3320.3980.3590.6371.0000.3170.2050.5780.6070.6330.6310.3300.3210.2530.3020.3240.3150.2570.1090.0570.5770.0460.0690.0080.0600.0850.0530.0670.0640.5770.0230.5780.0900.5780.5790.5840.5780.0070.4990.0000.0000.0000.5770.0000.0000.0001.0000.0310.0120.0480.000NaN0.0000.4690.4420.3510.3520.0810.0100.0760.0000.0770.0000.0000.0000.0000.0000.0760.0600.0390.0410.0370.0020.0500.0160.0130.0800.074
OUTRO_SIN0.0130.0140.0670.0000.0480.1090.0090.0320.0240.0640.0470.0110.0070.1180.0331.0000.0680.0700.2050.2140.2320.1740.2070.1690.3070.3171.0000.7200.7070.1790.2410.6080.6110.1790.2120.2210.6080.1940.1750.5440.1110.7100.5800.0670.0500.0600.1700.0580.0670.0850.5780.5770.0460.0300.0260.0740.0980.0060.7070.7000.7870.5760.0000.0000.4990.9980.7070.2240.0530.0160.0470.000NaN0.0000.2570.2780.2090.2600.1080.0230.0890.0830.0780.7070.0000.0000.6300.0000.1400.0760.0500.0520.0500.0130.0450.0470.0390.0960.000
PUERPERA0.0070.0070.0321.0000.0320.0500.0330.0330.0850.0250.0520.0270.0180.0560.0140.0000.0300.0380.1380.1440.1780.1870.2300.1450.2540.2050.7201.0000.7750.3960.6840.7830.6900.6630.6650.6800.6760.4500.3100.5330.0440.6020.6040.0560.0800.0500.0720.0230.0350.0430.5010.5780.0440.0980.1240.1820.2210.0540.7070.6920.8650.7030.0000.5680.8640.8120.5390.7040.0200.0310.0431.0000.0001.0000.2150.2260.1530.1860.0570.0000.0600.0350.0581.0001.0001.0001.0001.0000.0840.1430.1070.1040.0770.0310.0450.0060.0500.0820.126
FATOR_RISC0.0360.0380.0710.7070.1330.0780.4480.7270.1170.4110.4750.5000.0000.1090.0381.0000.0710.0390.1320.1050.0370.0570.0220.1090.0170.5780.7070.7751.0000.5780.7070.7750.5780.6120.7070.7070.5780.5000.4090.5770.0740.8170.7070.0670.0480.0280.1780.1170.1610.5800.7070.5010.7110.1220.7140.7110.7080.5800.7070.7050.8060.7070.1410.7070.5000.9990.7071.0000.1920.7070.7280.0001.0000.0060.0210.0710.5780.0310.7350.0140.1830.1970.1190.7070.0000.0000.6670.0000.0200.0140.0500.0490.1030.7070.7590.0050.2910.0650.018
CARDIOPATI0.0280.0290.0461.0000.0730.0680.0370.5850.1180.0520.5940.0270.0000.0830.0161.0000.0470.0480.1430.1470.1780.1960.2180.1850.2410.6070.1790.3960.5781.0000.7140.7060.5270.4650.5460.4770.4740.5190.4260.2640.0550.5780.0640.0510.0170.0280.0870.0400.0430.0850.5770.0380.5780.0830.5810.5790.5810.5770.0180.7060.0000.0000.0000.7060.0051.0000.0000.4370.1330.0300.0971.0000.0001.0000.2030.2410.1890.1870.1390.0230.0740.1470.0931.0001.0001.000NaN1.0000.0940.0680.0540.0550.0610.0300.1930.0200.0410.0810.075
HEMATOLOGI0.0100.0080.0491.0000.0460.0580.0160.5000.0410.0250.5790.0220.0000.0750.0151.0000.0460.0530.1970.1910.2380.2350.2670.2180.3270.6330.2410.6840.7070.7141.0000.8190.6280.7280.7210.7480.5970.6000.4900.3200.0510.5770.0560.0490.0060.0300.0800.0370.0480.0450.5770.0400.5780.1040.5780.5790.5890.5770.0000.6910.0000.0000.0000.7010.0001.0000.0000.4350.0190.0270.0411.0000.0001.0000.2760.2910.2480.2480.0560.0040.0790.0520.0911.0001.0001.000NaN1.0000.0910.0560.0530.0490.0650.0250.0300.0090.0300.0880.094
SIND_DOWN0.0140.0130.0301.0000.0410.0430.0180.5060.0530.0230.5070.0190.0000.0560.0141.0000.0360.0400.2010.1870.2280.2440.2930.2260.3230.6310.6080.7830.7750.7060.8191.0000.7580.7160.7210.7380.7360.5770.4860.6300.0450.7070.0770.0590.0000.0360.0610.0380.0350.0480.7070.5010.5780.1040.5790.5790.5820.5000.7070.6760.6220.7001.0000.7020.7020.9930.7060.4360.0660.0280.0421.0000.0001.0000.2680.2870.1910.2340.0660.0000.0760.0000.0841.0001.0001.0001.0001.0000.0830.0340.0550.0620.0710.0270.1000.0000.0000.0920.051
HEPATICA0.0110.0110.0311.0000.0380.0590.0300.0240.0430.0270.0420.0170.0000.0580.0121.0000.0450.0470.1930.1910.2440.2430.2800.2250.3390.3300.6110.6900.5780.5270.6280.7581.0000.5570.5440.5910.7600.6140.5010.6360.0500.5770.0540.0510.0000.0390.0620.0360.0410.0380.5770.5780.0230.1080.0370.0730.2040.0050.7070.9880.6140.7001.0000.0000.7020.9930.7060.4360.0170.0250.0541.0000.0001.0000.2860.3030.2080.2560.0600.0120.0780.0000.0921.0001.0001.0001.0001.0000.0800.0410.0620.0630.0640.0250.0320.0020.0000.0900.144
ASMA0.0460.0490.0321.0000.1070.0720.0080.0530.0720.0400.1110.0000.0000.0800.0171.0000.0660.0500.2080.2440.2440.2610.2950.2250.3250.3210.1790.6630.6120.4650.7280.7160.5571.0000.7810.7950.4170.7340.4460.2460.0490.5760.0310.0580.0160.0380.0990.0730.1030.1250.0230.0280.5790.5840.0380.0850.1510.0050.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.5880.0320.1501.0000.0001.0000.2800.2940.2440.2440.1230.7070.5930.7060.1370.7070.9980.0910.0001.0000.1060.0000.0650.0610.0570.0090.1380.0030.0000.0800.082
DIABETES0.0220.0220.0491.0000.0840.0610.0320.0940.0770.0330.1680.0310.0210.0700.0101.0000.0460.0420.1160.1540.1950.1730.1990.1660.2530.2530.2120.6650.7070.5460.7210.7210.5440.7811.0000.7930.5070.7280.4640.3050.0520.5790.1300.0690.1560.0430.0890.0480.0330.0840.0120.0210.5790.5800.0640.0260.1440.0190.0490.0000.7760.1010.9260.4190.2670.6970.1190.3970.5860.0340.0771.0000.0001.0000.2250.2520.2020.2010.1260.7080.5800.7120.0721.0000.9980.0911.0001.0000.0880.1850.1540.1530.0690.0320.1820.0150.0330.0910.000
NEUROLOGIC0.0120.0110.0301.0000.0470.0480.0210.0370.0390.0310.0590.0190.0000.0550.0131.0000.0390.0390.2060.1880.2210.2220.2630.2170.3100.3020.2210.6800.7070.4770.7480.7380.5910.7950.7931.0000.5530.7430.4650.2990.0540.5780.0570.0520.0000.0370.0680.0340.0350.0480.0090.0140.5780.5820.0440.0590.1330.0190.0000.0000.0000.0001.0000.0000.0001.0000.0000.4360.5780.0260.0441.0000.0001.0000.2560.2750.2310.2320.0540.7070.5800.7060.0861.0000.9980.9131.0001.0000.1120.0220.0510.0580.0680.0270.0280.0050.0340.0830.088
IMUNODEPRE0.0180.0170.0380.0130.0470.0700.0250.0400.0430.0270.0730.0200.0040.0680.033NaN0.0660.0450.2070.1840.2460.2320.2640.2160.3360.3240.6080.6760.5780.4740.5970.7360.7600.4170.5070.5531.0000.5800.4700.6270.0580.5840.0580.0500.0000.0310.0770.0340.0510.0460.5770.5780.0410.1040.0500.1060.1310.0160.7070.6930.6280.7001.0000.0000.7020.9931.0000.4360.0450.0320.0661.0000.0001.0000.2850.2950.2100.2560.0930.0110.0770.0650.0930.7070.2580.0001.0001.0000.0890.0650.0430.0560.0580.0260.0370.0110.0190.0920.155
RENAL0.0170.0180.0361.0000.0470.0560.0220.0490.0450.0180.0770.0030.0000.0560.0131.0000.0600.0460.1870.1900.2390.2390.2700.2130.3270.3150.1940.4500.5000.5190.6000.5770.6140.7340.7280.7430.5801.0000.4930.3250.0540.5780.0720.0530.0220.0380.0640.0540.0440.0380.0120.0180.5780.5830.0430.0570.1410.0000.0000.3310.0000.1540.9260.1340.0900.2040.0970.1450.5790.0100.0591.0000.0001.0000.2740.2900.2470.2470.0730.7070.5810.7060.1061.0000.9980.0911.0001.0000.0740.0000.0580.0590.0680.0080.0600.0120.0000.0960.112
OBESIDADE0.0140.0150.3351.0000.0320.5810.5790.0580.5820.0320.5820.5780.5770.5800.0141.0000.0390.0530.1280.1640.2050.2070.2390.1970.2660.2570.1750.3100.4090.4260.4900.4860.5010.4460.4640.4650.4700.4931.0000.2950.0540.0550.0480.0480.0000.5780.5810.0490.5780.0430.0080.5780.0230.0830.0470.0780.0930.0160.0000.5310.0000.2430.9260.2410.1570.6960.7090.2730.5780.5780.5781.0000.0001.0000.2340.2620.2110.2090.0700.0110.0790.0000.0741.0001.0001.000NaN1.0000.0570.0000.0520.0590.5790.5780.5800.0060.0310.0750.100
OUT_MORBI0.0090.0120.4501.0000.0700.0770.5000.0740.0270.0290.5020.6320.5000.6380.5001.0000.0470.0520.5830.0740.0980.0800.5820.7100.1230.1090.5440.5330.5770.2640.3200.6300.6360.2460.3050.2990.6270.3250.2951.0000.7090.5780.5790.5790.7070.5790.5880.5790.0440.0530.5770.5770.0570.0450.0110.1190.0710.0300.7070.5290.4410.8150.9430.5740.8630.9951.0000.7040.5800.0160.5790.000NaN0.0000.1210.1030.0980.1210.0940.0280.0610.0310.0391.0001.0001.0000.8941.0000.0750.0940.0710.0540.0750.0090.0290.0430.0000.0790.051
VACINA0.0410.0430.5081.0000.0620.1360.5770.0700.0550.1190.1740.5770.0060.5980.580NaN0.1190.1660.5780.0470.0780.0370.0390.0700.0610.0570.1110.0440.0740.0550.0510.0450.0500.0490.0520.0540.0580.0540.0540.7091.0000.4120.6350.2220.5810.0290.5980.0830.0730.1550.0200.0190.0410.0630.0680.0770.0000.0090.0000.4860.0000.5760.5470.5760.5770.9981.0000.9990.5790.0170.5780.0001.0000.0000.0690.0600.0600.0640.1210.0400.0850.1200.0521.0001.0001.0001.0000.1090.2240.1010.0890.1040.0890.0120.1380.0140.0640.2300.000
MAE_VAC0.0250.0260.1270.9990.1090.1710.0000.6390.0000.0760.5040.0000.0000.2080.0640.0000.0880.1190.0460.0170.0620.0260.0230.0280.0340.5770.7100.6020.8170.5780.5770.7070.5770.5760.5790.5780.5840.5780.0550.5780.4121.0000.4230.1600.0600.0190.2780.0740.0750.1040.7070.4510.7090.5780.7040.5640.5730.7091.0000.9350.8160.9941.0000.9890.9970.9890.9991.0000.5780.0370.0531.0000.0001.0000.0370.0360.0410.0450.1030.7080.5780.7050.0740.9960.9990.0000.5771.0000.3830.0000.1350.1640.1600.0140.0680.0490.2180.1730.458
M_AMAMENTA0.0190.0170.4601.0000.1270.2200.5770.6180.5770.0810.1180.5770.5770.2810.0950.0000.0950.1060.7070.0280.0370.0320.0740.0690.0420.0460.5800.6040.7070.0640.0560.0770.0540.0310.1300.0570.0580.0720.0480.5790.6350.4231.0000.6020.7080.5810.6340.0780.1090.1520.0310.0330.0720.0000.0540.3520.1440.0001.0001.0000.8161.0001.0000.9870.9970.9880.9990.9940.0560.0210.0191.0000.0001.0000.0520.0440.0440.0940.2160.0300.0510.0000.0581.0001.0001.0001.000NaN0.3440.5910.5980.5980.1960.0050.5790.0460.3000.2430.415
ANTIVIRAL0.0430.0440.4161.0000.0700.1370.0040.5800.5040.0550.5900.7070.7070.5980.0540.0000.2300.1780.5800.0800.0390.0370.0840.5790.0700.0690.0670.0560.0670.0510.0490.0590.0510.0580.0690.0520.0500.0530.0480.5790.2220.1600.6021.0001.0000.7080.5980.5870.1070.2160.0270.0230.0960.1330.0250.0460.1180.0930.0220.1980.7220.0680.4470.5790.5770.9991.0000.9990.1390.0080.0800.0001.0000.0000.0330.0470.0320.0360.1520.0620.3490.0000.2771.0001.0001.0001.0000.0000.1370.5900.5900.5900.1490.0130.5830.0280.0260.4860.071
TP_ANTIVIR0.0390.0400.4211.0000.1000.1170.5000.5790.5000.0610.5800.7070.7070.5960.012NaN0.0120.0690.7070.0090.0360.1080.1260.5870.0200.0080.0500.0800.0480.0170.0060.0000.0000.0160.1560.0000.0000.0220.0000.7070.5810.0600.7081.0001.0000.6330.5980.5780.0750.0250.0570.0000.1310.0110.0000.0750.0000.0090.0000.0000.9350.0001.0000.9960.7030.6890.7050.9950.0700.0450.0001.0000.0001.0000.0460.0300.0450.0650.0500.0670.0970.0350.0800.0001.0000.0001.0001.0000.1040.6260.5810.5920.1820.0000.5780.0840.0000.0670.225
HOSPITAL0.0130.0120.3481.0000.0620.4110.5000.5780.5780.0090.7750.8170.8160.7770.0141.0000.0540.0360.5010.0630.0610.0810.0870.5830.0610.0600.0600.0500.0280.0280.0300.0360.0390.0380.0430.0370.0310.0380.5780.5790.0290.0190.5810.7080.6331.0000.8660.7070.5830.0610.5840.5780.0290.0490.0080.0380.0220.0370.0000.7010.7010.1570.6860.5140.5930.7210.8190.7200.5830.5770.5800.0001.0000.0000.0420.0570.0430.0470.0430.0040.2130.2710.2171.0001.0001.0001.0001.0000.0210.5820.5020.5020.5010.7070.7080.0330.0170.0580.034
SG_UF_INTE0.0810.0800.9331.0000.1891.0000.5780.4140.4110.3020.5230.4480.4640.9790.4161.0000.1350.1970.5870.0860.1340.1170.0840.1480.0660.0850.1700.0720.1780.0870.0800.0610.0620.0990.0890.0680.0770.0640.5810.5880.5980.2780.6340.5980.5980.8661.0000.5890.5180.1530.5900.4200.1890.0930.1430.2620.3580.0540.0000.6630.3910.5700.5840.4880.5010.6910.8150.6960.5910.5230.6400.0061.0000.0230.0670.1060.0880.0950.1350.1890.1860.1240.1011.0001.0001.0001.0000.5000.6140.6240.4440.4570.4120.7120.6380.1000.1400.1830.186
UTI0.0170.0200.2991.0000.0670.1050.0030.0290.0430.0530.7100.7070.7070.7150.0410.0000.1190.0860.0630.0930.0610.0550.0530.5830.0550.0530.0580.0230.1170.0400.0370.0380.0360.0730.0480.0340.0340.0540.0490.5790.0830.0740.0780.5870.5780.7070.5891.0000.3540.1280.5780.0340.0550.0280.0080.0360.1080.0050.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0600.0150.1710.000NaN0.0000.0490.0510.0470.0490.1890.0480.0300.0620.0281.0001.0001.0001.0000.0000.0640.0360.1010.1140.1000.0050.0680.0380.0250.1180.066
SUPORT_VEN0.0180.0210.5081.0000.0730.5180.5770.0490.5020.0620.5040.5000.5000.5180.039NaN0.0840.0610.0710.1150.0920.2020.2140.3140.0580.0670.0670.0350.1610.0430.0480.0350.0410.1030.0330.0350.0510.0440.5780.0440.0730.0750.1090.1070.0750.5830.5180.3541.0000.1880.0570.5020.0460.0560.0420.0510.0650.0450.0000.0000.0000.0000.0000.0000.0001.0001.0001.0000.5040.5000.5380.000NaN0.0000.0510.0660.0370.0330.2190.0620.0970.0960.0921.0001.0001.0001.0000.0000.1220.0700.0420.0620.5020.7070.5040.0710.0230.1120.089
RAIOX_RES0.0320.0300.1031.0000.0700.1380.5000.5850.0710.4140.1170.3780.0030.1480.0941.0000.1420.1110.0840.1060.0810.1140.1290.1080.0590.0640.0850.0430.5800.0850.0450.0480.0380.1250.0840.0480.0460.0380.0430.0530.1550.1040.1520.2160.0250.0610.1530.1280.1881.0000.0330.0300.0710.0430.0000.0480.0090.0390.0000.0000.0000.0000.0370.0000.0000.0000.0250.9980.0780.4470.4520.0001.0000.0110.0560.0580.5800.0730.4350.0780.1170.0340.0390.0231.0001.0000.0000.0000.1980.1700.0640.0770.0810.5770.4580.0340.1550.1690.152
AMOSTRA0.0190.0160.5041.0000.0840.0900.0050.5000.0050.0310.6330.5000.5000.5100.0281.0000.0200.0400.0070.0090.0170.0190.0280.0390.0150.5770.5780.5010.7070.5770.5770.7070.5770.0230.0120.0090.5770.0120.0080.5770.0200.7070.0310.0270.0570.5840.5900.5780.0570.0331.0000.7070.7070.0000.7070.7090.9990.5771.0000.7040.8050.9991.0000.9991.0000.4990.5001.0000.0930.3870.0230.000NaN0.0000.0130.0120.0070.0180.0580.0000.1950.2330.2221.0001.0001.0000.4581.0000.0320.0970.0780.0840.0650.0000.0260.0300.0230.0290.080
TP_AMOSTRA0.0120.0110.3830.0000.0180.3890.5000.0270.3780.0310.3790.3780.3780.3880.0281.0000.0270.0130.0180.0210.0120.0160.0160.0180.0100.0230.5770.5780.5010.0380.0400.5010.5780.0280.0210.0140.5780.0180.5780.5770.0190.4510.0330.0230.0000.5780.4200.0340.5020.0300.7071.0000.0270.0140.0860.1030.1960.0300.7070.5450.6800.5740.0000.1100.7060.9981.0000.4050.4090.4480.4480.0221.0000.0870.0230.0240.0230.0070.0360.0300.0170.0000.0160.7070.0001.0000.2800.0000.1800.0830.0400.0520.4110.5780.4480.0150.0020.0340.013
PCR_RESUL0.0750.0760.1121.0000.2460.1600.0100.5870.0400.0430.4130.0000.0000.1710.0900.0000.0810.0490.0780.0600.0510.0270.0490.0330.0240.5780.0460.0440.7110.5780.5780.5780.0230.5790.5790.5780.0410.5780.0230.0570.0410.7090.0720.0960.1310.0290.1890.0550.0460.0710.7070.0271.0000.7070.8160.7090.9340.8160.5001.0000.3340.7060.9921.0000.5001.0001.0001.0000.5950.1050.0700.0001.0000.7070.0330.0260.0440.0450.0700.7080.5810.7070.0511.0000.9990.9310.9490.0000.2000.1600.0890.1110.0880.0090.0800.0250.0140.0900.098
POS_PCRFLU0.1180.1190.0591.0000.0720.0850.0100.1720.0790.0270.1290.0000.0000.0830.0280.0000.0380.0510.0900.0580.0730.0980.1180.0710.0920.0900.0300.0980.1220.0830.1040.1040.1080.5840.5800.5820.1040.5830.0830.0450.0630.5780.0000.1330.0110.0490.0930.0280.0560.0430.0000.0140.7071.0001.0001.0000.9990.7841.0000.9950.9890.9990.9910.9991.0001.0001.0001.0000.8130.0130.0581.0000.0001.0000.0700.0710.0460.0480.1070.7070.7920.7050.5391.0000.9980.8160.9431.0000.0830.0100.0720.0830.0970.0110.1460.0170.0690.0820.000
TP_FLU_PCR0.1240.1230.0901.0000.0220.1120.0000.5810.0660.0680.5810.0000.0000.1360.0150.0000.0220.0070.0440.0170.0330.0430.0000.0480.0220.5780.0260.1240.7140.5810.5780.5790.0370.0380.0640.0440.0500.0430.0470.0110.0680.7040.0540.0250.0000.0080.1430.0080.0420.0000.7070.0860.8161.0001.0000.8210.9990.8170.9990.9350.9350.9781.0000.9830.0001.0001.0001.0000.0000.0000.0381.0000.0001.0000.0310.0300.0150.0130.0610.0510.0000.8870.0001.0001.0001.000NaNNaN0.0490.0770.0740.0400.0380.0000.1320.0060.1550.0090.117
PCR_FLUASU0.0780.0680.1741.0000.1120.2390.0430.5780.0270.0970.3810.0000.0000.2490.0840.0000.0150.0620.0450.0380.0520.0320.0370.0620.0180.5790.0740.1820.7110.5790.5790.5790.0730.0850.0260.0590.1060.0570.0780.1190.0770.5640.3520.0460.0750.0380.2620.0360.0510.0480.7090.1030.7091.0000.8211.0001.0000.7100.9870.6321.0000.756NaN0.9050.4391.0001.0001.0000.0550.0630.0580.147NaN0.3930.1060.1110.0390.0460.0550.0740.0000.1990.0001.0001.0001.0000.000NaN0.0000.0000.0960.0000.0000.0160.0580.0050.0610.0220.000
PCR_FLUBLI0.0560.0560.1521.0000.0770.3300.0130.5770.0000.0820.4110.0000.0000.3400.0000.0000.1090.0660.1320.0960.0510.0390.0610.0350.0710.5840.0980.2210.7080.5810.5890.5820.2040.1510.1440.1330.1310.1410.0930.0710.0000.5730.1440.1180.0000.0220.3580.1080.0650.0090.9990.1960.9340.9990.9991.0001.0000.7080.9921.0000.0000.0001.0000.8661.0001.0001.0001.0000.0500.0660.1040.706NaN0.9850.4100.4110.0280.0000.1250.0420.1020.0000.1181.0001.0000.000NaN0.0000.0000.3540.1710.2340.2360.0000.0440.0400.0000.115NaN
POS_PCROUT0.0870.0880.0361.0000.0430.0500.0100.5880.0710.0270.5080.0080.0080.0550.0150.0000.0110.0120.0320.0160.0460.0370.0510.0270.0160.5780.0060.0540.5800.5770.5770.5000.0050.0050.0190.0190.0160.0000.0160.0300.0090.7090.0000.0930.0090.0370.0540.0050.0450.0390.5770.0300.8160.7840.8170.7100.7081.0001.0000.9980.9951.0000.4801.0000.5000.4990.5001.0000.6510.0080.0521.0000.0001.0000.0380.0290.0250.0250.0810.0410.5800.0000.5530.1091.0001.0000.0001.0000.0430.0120.0580.0680.0590.0090.1100.0250.0210.0200.000
PCR_VSR0.0100.0100.0001.0001.0000.0690.0000.0040.0000.0000.0280.0000.0000.1010.0140.0000.0000.0000.0000.0150.0000.0020.0040.0000.0000.0070.7070.7070.7070.0180.0000.7070.7070.0000.0490.0000.7070.0000.0000.7070.0001.0001.0000.0220.0000.0000.0000.0040.0000.0001.0000.7070.5001.0000.9990.9870.9921.0001.0001.0000.9571.0000.2750.4940.4830.4910.4981.0001.0001.0001.0001.0000.0001.0001.0000.0000.0001.0001.0001.0001.0001.0001.0000.4891.000NaNNaN1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
PCR_PARA10.0000.0000.4791.0001.0000.2340.0000.3970.0690.0790.5230.7011.0000.5620.525NaN0.0000.0000.0390.0860.0000.0000.0030.0000.0000.4990.7000.6920.7050.7060.6910.6760.9880.0000.0000.0000.6930.3310.5310.5290.4860.9351.0000.1980.0000.7010.6630.0000.0000.0000.7040.5451.0000.9950.9350.6321.0000.9981.0001.0000.7000.8161.0000.9430.9490.8660.9860.2180.9960.7010.9951.0000.0001.0001.0000.0000.0001.0001.0001.0001.0000.0001.0001.0001.0001.000NaN0.0001.000NaN1.0001.0001.0001.0001.0001.0001.0001.0000.000
PCR_PARA20.1100.0000.4591.0001.0000.6970.1130.7010.6890.0000.0000.7010.9960.7540.194NaN0.0000.7020.7000.0000.0940.0000.1690.0000.0000.0000.7870.8650.8060.0000.0000.6220.6140.0000.7760.0000.6280.0000.0000.4410.0000.8160.8160.7220.9350.7010.3910.0000.0000.0000.8050.6800.3340.9890.9351.0000.0000.9950.9570.7001.0000.7070.0000.8160.7070.8660.9770.9491.0001.0001.0001.000NaN1.0000.3590.0000.0000.5480.5111.0000.0000.000NaNNaNNaN0.000NaNNaN1.000NaN0.7750.8661.0001.0000.9861.0001.0001.0000.000
PCR_PARA30.0850.0730.4971.0001.0000.3440.0110.0000.0570.0000.0710.7050.0000.6040.511NaN0.0000.0000.0250.1250.0000.0000.0000.0000.0000.0000.5760.7030.7070.0000.0000.7000.7000.0000.1010.0000.7000.1540.2430.8150.5760.9941.0000.0680.0000.1570.5700.0000.0000.0000.9990.5740.7060.9990.9780.7560.0001.0001.0000.8160.7071.0001.0001.0001.0001.0001.0000.4780.9980.1890.9990.499NaN0.4261.0000.0000.0001.0001.0001.0001.0000.0001.0000.000NaN0.0000.2750.0001.0001.0000.9791.0000.9840.0000.9991.0001.0001.0000.000
PCR_PARA40.0880.2470.3921.0001.0000.5080.0000.0000.2540.0000.4710.6860.0000.7000.806NaN0.0000.0000.0000.4440.0000.0000.0000.0000.0000.0000.0000.0000.1410.0000.0001.0001.0000.0000.9261.0001.0000.9260.9260.9430.5471.0001.0000.4471.0000.6860.5840.0000.0000.0371.0000.0000.9920.9911.000NaN1.0000.4800.2751.0000.0001.0001.0000.8660.8160.8160.9260.8940.9840.4580.9910.480NaN0.0001.0001.0001.0001.0001.0001.0000.0000.000NaNNaN0.0000.0000.000NaN1.0001.0000.8661.0000.9260.0000.9771.000NaN1.0000.000
PCR_ADENO0.0370.0300.4051.0001.0000.0000.0000.7060.5060.0450.7070.7060.5760.5680.5011.0000.0000.2540.5780.0650.0220.0000.0000.0000.0000.5770.0000.5680.7070.7060.7010.7020.0000.0000.4190.0000.0000.1340.2410.5740.5760.9890.9870.5790.9960.5140.4880.0000.0000.0000.9990.1101.0000.9990.9830.9050.8661.0000.4940.9430.8161.0000.8661.0001.0001.0000.9991.0000.9990.2030.9990.499NaN0.4450.0821.0001.0000.2130.3441.0001.000NaN1.0001.0001.0000.0000.0000.2750.0000.9650.9940.9910.9870.0000.9991.0001.0001.0001.000
PCR_METAP0.0320.0300.5001.0001.0000.1470.0000.5770.5010.0000.0000.8160.7070.6000.502NaN0.0000.1440.5770.0820.0290.0000.0000.0000.0000.0000.4990.8640.5000.0050.0000.7020.7020.0000.2670.0000.7020.0900.1570.8630.5770.9970.9970.5770.7030.5930.5010.0000.0000.0001.0000.7060.5001.0000.0000.4391.0000.5000.4830.9490.7071.0000.8161.0001.0001.0001.0001.0000.9990.1790.9990.500NaN0.4480.0920.0000.0000.1920.2581.0001.0001.0001.0000.0911.000NaNNaN0.0000.0000.9710.9930.9930.9950.0001.0001.0001.0001.0001.000
PCR_BOCA0.1350.1000.5721.0001.0000.3080.0000.5760.5840.0000.0000.9990.9990.7200.583NaN0.0000.3480.7060.0000.0780.0060.0590.0000.0000.0000.9980.8120.9991.0001.0000.9930.9930.0000.6971.0000.9930.2040.6960.9950.9980.9890.9880.9990.6890.7210.6910.0001.0000.0000.4990.9981.0001.0001.0001.0001.0000.4990.4910.8660.8661.0000.8161.0001.0001.0001.0001.0000.9980.2860.9981.0000.0001.0000.1310.0000.0000.3270.4361.0001.0000.0001.0000.0001.0000.000NaN0.0000.0000.8660.9790.9861.0001.0000.9991.0001.0001.0001.000
PCR_RINO0.0000.0000.5261.0001.0000.4200.5000.5780.7070.0000.7060.9130.8660.8740.5781.0000.0470.1350.7070.0000.0190.0120.0270.0150.0000.0000.7070.5390.7070.0000.0000.7060.7060.0000.1190.0001.0000.0970.7091.0001.0000.9990.9991.0000.7050.8190.8150.0001.0000.0250.5001.0001.0001.0001.0001.0001.0000.5000.4980.9860.9771.0000.9260.9991.0001.0001.0001.0001.0000.7101.0001.0000.0001.0000.0230.0000.0000.1120.1151.0001.0001.0001.0000.4581.0000.0000.0001.0000.0000.9910.7180.8640.9991.0001.0001.0001.0001.0001.000
PCR_OUTRO0.0230.0000.7041.0001.0000.0560.5770.8150.5930.5750.1321.0001.0000.9920.5821.0000.1020.2360.7350.2850.0700.1840.3150.1910.2841.0000.2240.7041.0000.4370.4350.4360.4360.0000.3970.4360.4360.1450.2730.7040.9991.0000.9940.9990.9950.7200.6960.0001.0000.9981.0000.4051.0001.0001.0001.0001.0001.0001.0000.2180.9490.4780.8941.0001.0001.0001.0001.0000.7160.7090.9991.0000.0001.0000.0710.0660.9990.2070.7590.0001.000NaN1.0001.0001.0000.0000.000NaN0.0000.9530.6900.7280.8010.9990.9991.0000.9721.0001.000
CLASSI_FIN0.1020.1030.3851.0000.3270.3970.4480.1920.3880.0380.4740.5350.4080.5480.5031.0000.0730.0340.0900.1060.0850.0660.0960.0550.0270.0310.0530.0200.1920.1330.0190.0660.0170.5880.5860.5780.0450.5790.5780.5800.5790.5780.0560.1390.0700.5830.5910.0600.5040.0780.0930.4090.5950.8130.0000.0550.0500.6511.0000.9961.0000.9980.9840.9990.9990.9981.0000.7161.0000.4200.5841.0000.0001.0000.0580.0670.0520.0650.1520.7090.8090.7070.6281.0001.0000.9680.9471.0000.1830.1740.0910.1260.4510.5000.4770.0190.0370.1090.068
CRITERIO0.0410.0370.3631.0000.0610.4260.7750.7070.4470.4100.4080.7070.6320.6460.0321.0000.0190.0400.0250.0240.0140.0250.0220.0200.0180.0120.0160.0310.7070.0300.0270.0280.0250.0320.0340.0260.0320.0100.5780.0160.0170.0370.0210.0080.0450.5770.5230.0150.5000.4470.3870.4480.1050.0130.0000.0630.0660.0081.0000.7011.0000.1890.4580.2030.1790.2860.7100.7090.4201.0000.7071.0000.0001.0000.0130.0330.5770.0070.5010.0130.0260.0480.0471.0001.0001.0001.0001.0000.0720.0590.0740.0550.4170.8660.7750.7070.2050.0190.000
EVOLUCAO0.0290.0310.4511.0000.0700.3870.7750.7130.4130.4100.4180.7560.6320.7130.5011.0000.0600.0570.1080.1610.0450.0650.0460.0910.0410.0480.0470.0430.7280.0970.0410.0420.0540.1500.0770.0440.0660.0590.5780.5790.5780.0530.0190.0800.0000.5800.6400.1710.5380.4520.0230.4480.0700.0580.0380.0580.1040.0521.0000.9951.0000.9990.9910.9990.9990.9981.0000.9990.5840.7071.0001.0000.0001.0000.0250.0570.5770.0130.5120.0220.1120.0590.0791.0001.0001.0001.0001.0000.1180.0560.0700.0780.4190.8660.7820.7070.2060.0570.095
HISTO_VGM0.0000.0000.0071.0001.0000.0060.0010.0000.0030.0060.0000.0000.0000.0050.0040.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0001.0000.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.0000.0001.0001.0000.0001.0000.0000.0060.0000.0000.0000.0000.0220.0001.0001.0000.1470.7061.0001.0001.0001.0000.4990.4800.4990.5001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.4721.0001.0001.0001.0001.0000.0001.0001.0001.0001.0001.000
PAIS_VGM1.0001.0001.0000.0000.0001.0001.0001.0001.0001.000NaN1.0001.0001.0001.0000.0001.0001.000NaNNaN1.0001.0001.0001.000NaNNaNNaN0.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000NaN1.0000.0000.0001.0000.0001.0001.000NaNNaN1.000NaN1.0001.0000.0000.000NaNNaN0.0000.0000.000NaNNaNNaNNaNNaN0.0000.0000.0000.0000.0000.0001.0001.0001.000NaNNaNNaN0.0000.0000.0000.0000.0000.0000.0000.0000.0000.000NaN0.0000.000NaN0.000NaNNaNNaN0.0000.0000.0000.000
PCR_SARS20.0000.0000.0071.0001.0000.0240.0000.0000.0000.0290.0001.0001.0000.0200.0230.0000.0000.0000.0000.0100.0000.0000.0000.0000.0000.0000.0001.0000.0061.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.0000.0001.0001.0000.0001.0000.0000.0230.0000.0000.0110.0000.0870.7071.0001.0000.3930.9851.0001.0001.0001.0000.4260.0000.4450.4481.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.0001.0001.0001.0001.0001.0001.0001.0001.0000.000NaN1.0001.0001.0000.9981.0000.9980.0001.0001.0001.0001.0001.000
DOR_ABD0.0150.0160.0481.0000.0320.0670.0110.0760.0320.0380.0530.0040.0000.0660.0140.0000.0550.0490.2730.2740.5190.3330.2990.2720.4510.4690.2570.2150.0210.2030.2760.2680.2860.2800.2250.2560.2850.2740.2340.1210.0690.0370.0520.0330.0460.0420.0670.0490.0510.0560.0130.0230.0330.0700.0310.1060.4100.0381.0001.0000.3591.0001.0000.0820.0920.1310.0230.0710.0580.0130.0251.000NaN1.0001.0000.7080.4310.5230.0500.0000.0500.0300.0561.0001.0001.0001.0001.0000.0720.0530.0330.0320.0290.0100.0510.0030.0220.0430.047
FADIGA0.0220.0220.0731.0000.0410.1050.0140.0570.0540.0500.0680.0080.0000.1050.0151.0000.0590.0510.2860.2930.4240.3020.3490.3140.4390.4420.2780.2260.0710.2410.2910.2870.3030.2940.2520.2750.2950.2900.2620.1030.0600.0360.0440.0470.0300.0570.1060.0510.0660.0580.0120.0240.0260.0710.0300.1110.4110.0290.0000.0000.0000.0001.0001.0000.0000.0000.0000.0660.0670.0330.0571.000NaN1.0000.7081.0000.3900.4740.0890.0110.0880.0410.0900.0001.0001.0000.0001.0000.1380.0870.0470.0540.0380.0130.0870.0080.0100.0610.060
PERD_OLFT0.0250.0220.0571.0000.0370.0710.5770.5800.0420.5780.0630.5770.0000.0860.008NaN0.0500.0500.2290.2320.5070.2770.2540.2350.3530.3510.2090.1530.5780.1890.2480.1910.2080.2440.2020.2310.2100.2470.2110.0980.0600.0410.0440.0320.0450.0430.0880.0470.0370.5800.0070.0230.0440.0460.0150.0390.0280.0250.0000.0000.0000.0001.0001.0000.0000.0000.0000.9990.0520.5770.5770.000NaN0.0000.4310.3901.0000.7300.5780.0010.0470.0480.0520.0001.0001.0000.0001.0000.0810.0670.0200.0270.0780.7070.5790.0120.2570.0310.051
PERD_PALA0.0290.0260.0631.0000.0400.0920.0100.0670.0470.0430.0770.0230.0230.0920.011NaN0.0510.0600.2310.2320.5030.2770.2540.2380.3530.3520.2600.1860.0310.1870.2480.2340.2560.2440.2010.2320.2560.2470.2090.1210.0640.0450.0940.0360.0650.0470.0950.0490.0330.0730.0180.0070.0450.0480.0130.0460.0000.0251.0001.0000.5481.0001.0000.2130.1920.3270.1120.2070.0650.0070.0131.0000.0001.0000.5230.4740.7301.0000.0410.0030.0450.0300.0511.0001.0001.0001.0001.0000.0710.1050.0530.0580.0300.0020.0560.0090.0220.0330.043
TOMO_RES0.0320.0350.0851.0000.0690.1220.5780.5170.0950.4110.1470.3780.0060.1300.084NaN0.1430.1060.0640.0850.0510.0670.0730.0830.0770.0810.1080.0570.7350.1390.0560.0660.0600.1230.1260.0540.0930.0730.0700.0940.1210.1030.2160.1520.0500.0430.1350.1890.2190.4350.0580.0360.0700.1070.0610.0550.1250.0811.0001.0000.5111.0001.0000.3440.2580.4360.1150.7590.1520.5010.5121.0000.0001.0000.0500.0890.5780.0411.0000.0480.1430.0990.0991.0001.0001.0001.0001.0000.1390.1150.0800.0780.1060.7070.5310.0690.1900.1740.136
TP_TES_AN0.0290.0320.0551.0000.1190.1270.0040.0100.0360.0570.0510.0000.0000.1230.023NaN0.0160.0350.0130.0130.0000.0300.0270.0220.0080.0100.0230.0000.0140.0230.0040.0000.0120.7070.7080.7070.0110.7070.0110.0280.0400.7080.0300.0620.0670.0040.1890.0480.0620.0780.0000.0300.7080.7070.0510.0740.0420.0411.0001.0001.0001.0001.0001.0001.0001.0001.0000.0000.7090.0130.0221.0000.0001.0000.0000.0110.0010.0030.0481.0000.7090.7080.0321.0001.0000.9850.9821.0000.0460.3140.1730.1700.1810.0130.0000.0060.0620.0590.000
POS_AN_FLU0.1800.1850.1001.0000.0280.1920.0100.1240.0480.0530.1120.0000.0000.1900.0380.0000.1060.0810.1170.0690.1070.1020.1160.1230.0670.0760.0890.0600.1830.0740.0790.0760.0780.5930.5800.5800.0770.5810.0790.0610.0850.5780.0510.3490.0970.2130.1860.0300.0970.1170.1950.0170.5810.7920.0000.0000.1020.5801.0001.0000.0001.0000.0001.0001.0001.0001.0001.0000.8090.0260.1121.0000.0001.0000.0500.0880.0470.0450.1430.7091.0001.0000.6631.0001.0000.9670.9801.0000.1660.0540.1400.1470.1250.0130.0720.0490.1130.1740.093
TP_FLU_AN0.2550.2450.1251.0000.0050.1590.0000.0000.0530.0080.1070.0000.0000.1580.0000.0000.0000.0420.0320.0490.0720.1350.0920.1340.0000.0000.0830.0350.1970.1470.0520.0000.0000.7060.7120.7060.0650.7060.0000.0310.1200.7050.0000.0000.0350.2710.1240.0620.0960.0340.2330.0000.7070.7050.8870.1990.0000.0001.0000.0000.0000.0000.000NaN1.0000.0001.000NaN0.7070.0480.0591.0000.0001.0000.0300.0410.0480.0300.0990.7081.0001.0000.0490.9950.9870.957NaNNaN0.1090.0000.1390.1390.1160.0000.0320.0000.1590.0000.000
POS_AN_OUT0.1790.1860.0811.0000.0030.1300.0100.0950.0350.0250.0810.0080.0080.1280.0250.0000.0280.0540.0730.0550.0840.1160.1270.1410.0830.0770.0780.0580.1190.0930.0910.0840.0920.1370.0720.0860.0930.1060.0740.0390.0520.0740.0580.2770.0800.2170.1010.0280.0920.0390.2220.0160.0510.5390.0000.0000.1180.5531.0001.000NaN1.000NaN1.0001.0001.0001.0001.0000.6280.0470.0791.0000.0001.0000.0560.0900.0520.0510.0990.0320.6630.0491.0001.0001.0001.0001.0001.0000.1170.1380.1160.1350.0930.0080.0400.0230.0000.0620.000
AN_SARS20.0160.0190.0001.0001.0000.0540.0020.0000.0000.0000.0000.0000.0000.0540.0180.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.7071.0000.7071.0001.0001.0001.0000.7071.0001.0000.7071.0001.0001.0001.0000.9961.0001.0000.0001.0001.0001.0001.0000.0231.0000.7071.0001.0001.0001.0001.0000.1090.4891.000NaN0.000NaN1.0000.0910.0000.4581.0001.0001.0001.0001.0000.0001.0001.0000.0000.0001.0001.0001.0001.0000.9951.0001.0000.4830.0001.000NaN0.0501.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
AN_VSR0.0600.0390.0690.4981.0000.1210.0000.0190.0000.0001.0000.0000.0000.1200.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0001.0001.0001.0001.0000.9980.9980.9980.2580.9981.0001.0001.0000.9991.0001.0001.0001.0001.0001.0001.0001.0001.0000.0000.9990.9981.0001.0001.0001.0001.0001.000NaNNaN0.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.0001.0001.0001.0001.0001.0001.0001.0001.0000.9871.0000.4831.0000.000NaN1.0000.0691.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
AN_PARA10.0000.0000.0000.0911.0000.8910.0000.0000.0000.2511.0001.0001.0000.8741.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0001.0001.0001.0001.0000.0910.0910.9130.0000.0911.0001.0001.0000.0001.0001.0000.0001.0001.0001.0001.0001.0001.0001.0000.9310.8161.0001.0000.0001.000NaN1.0000.0000.0000.0000.000NaN0.0000.0000.0000.9681.0001.0001.0000.0000.0001.0001.0001.0001.0001.0000.9850.9670.9571.0000.0000.0001.0000.0000.0001.000NaN0.0000.0000.0001.0001.0001.000NaN1.0000.000
AN_PARA30.0000.0000.3880.0001.0000.8880.0000.0000.0000.2130.1031.0001.0000.8880.2650.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.6301.0000.667NaNNaN1.0001.0000.0001.0001.0001.0001.000NaN0.8941.0000.5771.0001.0001.0001.0001.0001.0001.0000.0000.4580.2800.9490.943NaN0.000NaN0.000NaNNaNNaN0.2750.0000.000NaNNaN0.0000.0000.9471.0001.0001.0000.000NaN1.0000.0000.0001.0001.0000.9820.980NaN1.0001.000NaN0.0001.0001.0000.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.000
AN_ADENO0.0940.0000.0001.0001.0000.5060.0000.0000.3030.0001.0001.0001.0000.5060.2100.0000.0000.0000.1640.1910.0000.0000.0000.0000.0000.0000.0001.0000.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.1091.000NaN0.0001.0001.0000.5000.0000.0000.0001.0000.0000.0001.000NaNNaN0.0001.0001.0000.000NaN0.000NaN0.2750.0000.0001.000NaN1.0001.0001.0000.472NaN1.0001.0001.0001.0001.0001.0001.0001.000NaN1.000NaN1.0000.0001.0001.0001.0001.0000.8941.0000.8941.0000.9891.0001.0001.000NaN
TP_AM_SOR0.0710.0680.3170.0310.2410.5890.0140.1310.1050.1260.3040.0170.0170.5890.1020.0000.0610.0730.0840.0940.0820.0590.1690.0830.0900.0760.1400.0840.0200.0940.0910.0830.0800.1060.0880.1120.0890.0740.0570.0750.2240.3830.3440.1370.1040.0210.6140.0640.1220.1980.0320.1800.2000.0830.0490.0000.0000.0431.0001.0001.0001.0001.0000.0000.0000.0000.0000.0000.1830.0720.1181.0000.0001.0000.0720.1380.0810.0710.1390.0460.1660.1090.1170.0500.0691.0000.0001.0001.0000.4030.3670.4430.3090.0380.1120.0290.0300.1440.328
TP_SOR0.1030.1010.5531.0000.1390.3500.0390.5870.5020.1530.1920.5770.5770.4060.0000.0000.0820.1040.5780.0380.0480.0550.0780.0760.0330.0600.0760.1430.0140.0680.0560.0340.0410.0000.1850.0220.0650.0000.0000.0940.1010.0000.5910.5900.6260.5820.6240.0360.0700.1700.0970.0830.1600.0100.0770.0000.3540.0121.000NaNNaN1.0001.0000.9650.9710.8660.9910.9530.1740.0590.0561.0000.0001.0000.0530.0870.0670.1050.1150.3140.0540.0000.1381.0001.000NaN1.0001.0000.4031.0000.5060.5240.0680.0170.5820.0380.0000.1140.443
RES_IGG0.0630.0620.2861.0000.0910.2280.0070.5010.3800.0340.0570.5000.5780.2380.0921.0000.0430.0750.5780.0330.0460.0540.0740.0680.0360.0390.0500.1070.0500.0540.0530.0550.0620.0650.1540.0510.0430.0580.0520.0710.0890.1350.5980.5900.5810.5020.4440.1010.0420.0640.0780.0400.0890.0720.0740.0960.1710.0581.0001.0000.7750.9790.8660.9940.9930.9790.7180.6900.0910.0740.0701.000NaN0.9980.0330.0470.0200.0530.0800.1730.1400.1390.1161.0001.0000.0001.0000.8940.3670.5061.0000.7990.7370.0270.5780.0170.0490.1490.000
RES_IGM0.0690.0670.2841.0000.1020.2520.0250.4480.3810.0330.0690.4480.5010.2660.0950.0000.0480.0690.5780.0220.0780.0520.0730.0750.0360.0410.0520.1040.0490.0550.0490.0620.0630.0610.1530.0580.0560.0590.0590.0540.1040.1640.5980.5900.5920.5020.4570.1140.0620.0770.0840.0520.1110.0830.0400.0000.2340.0681.0001.0000.8661.0001.0000.9910.9930.9860.8640.7280.1260.0550.0781.0000.0001.0000.0320.0540.0270.0580.0780.1700.1470.1390.1351.0001.0000.0001.0001.0000.4430.5240.7991.0000.7260.0340.4100.0260.0440.1610.304
RES_IGA0.0600.0590.2661.0000.0820.4110.5070.0890.3550.0770.4110.4540.5040.4100.0910.0000.0540.0530.0340.0340.0480.0590.0780.0700.0370.0370.0500.0770.1030.0610.0650.0710.0640.0570.0690.0680.0580.0680.5790.0750.0890.1600.1960.1490.1820.5010.4120.1000.5020.0810.0650.4110.0880.0970.0380.0000.2360.0591.0001.0001.0000.9840.9260.9870.9951.0000.9990.8010.4510.4170.4191.000NaN0.9980.0290.0380.0780.0300.1060.1810.1250.1160.0931.0001.0000.0001.0000.8940.3090.0680.7370.7261.0000.5080.5810.0840.0960.1420.000
ESTRANG0.0050.0040.5001.0000.0220.5030.8660.7070.5770.5000.5000.8690.8200.8190.0101.0000.0130.0170.0190.0240.0120.0210.0230.0180.0170.0020.0130.0310.7070.0300.0250.0270.0250.0090.0320.0270.0260.0080.5780.0090.0120.0140.0050.0130.0000.7070.7120.0050.7070.5770.0000.5780.0090.0110.0000.0160.0000.0091.0001.0001.0000.0000.0000.0000.0001.0001.0000.9990.5000.8660.8660.000NaN0.0000.0100.0130.7070.0020.7070.0130.0130.0000.0081.0001.0001.0001.0001.0000.0380.0170.0270.0340.5081.0000.8660.7080.2880.0050.000
VACINA_COV0.0380.0380.4511.0000.0950.3850.7750.8090.5990.4110.5140.7560.7070.6380.0421.0000.0730.0590.5860.1180.0790.0210.0860.0410.0320.0500.0450.0450.7590.1930.0300.1000.0320.1380.1820.0280.0370.0600.5800.0290.1380.0680.5790.5830.5780.7080.6380.0680.5040.4580.0260.4480.0800.1460.1320.0580.0440.1101.0001.0000.9860.9990.9770.9991.0000.9991.0000.9990.4770.7750.7821.000NaN1.0000.0510.0870.5790.0560.5310.0000.0720.0320.0401.0001.0001.0001.0000.9890.1120.5820.5780.4100.5810.8661.0000.8440.2550.0900.028
FNT_IN_COV0.0210.0210.0681.0000.0060.0670.7070.7070.0110.7080.0170.7080.7080.7100.012NaN0.0280.0240.0120.0110.0070.0040.0150.0140.0150.0160.0470.0060.0050.0200.0090.0000.0020.0030.0150.0050.0110.0120.0060.0430.0140.0490.0460.0280.0840.0330.1000.0380.0710.0340.0300.0150.0250.0170.0060.0050.0400.0251.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.0190.7070.7071.0000.0001.0000.0030.0080.0120.0090.0690.0060.0490.0000.0231.0001.0001.0001.0001.0000.0290.0380.0170.0260.0840.7080.8441.0000.6420.0290.000
FAB_COVRF20.0340.0330.1421.0000.0350.1430.2880.2380.0370.1750.0400.4071.0000.1440.036NaN0.0150.0160.0360.0450.0180.0160.0050.0200.0190.0130.0390.0500.2910.0410.0300.0000.0000.0000.0330.0340.0190.0000.0310.0000.0640.2180.3000.0260.0000.0170.1400.0250.0230.1550.0230.0020.0140.0690.1550.0610.0000.0211.0001.0001.0001.000NaN1.0001.0001.0001.0000.9720.0370.2050.2061.0000.0001.0000.0220.0100.2570.0220.1900.0620.1130.1590.0001.0001.000NaN1.0001.0000.0300.0000.0490.0440.0960.2880.2550.6421.0000.0430.080
TRAT_COV0.0520.0550.0661.0000.0700.1780.0050.0510.0940.0930.1520.0000.0000.1750.0680.0000.2130.1890.0570.0670.0380.0450.0930.0610.0800.0800.0960.0820.0650.0810.0880.0920.0900.0800.0910.0830.0920.0960.0750.0790.2300.1730.2430.4860.0670.0580.1830.1180.1120.1690.0290.0340.0900.0820.0090.0220.1150.0201.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.1090.0190.0571.0000.0001.0000.0430.0610.0310.0330.1740.0590.1740.0000.0621.0001.0001.0001.0001.0000.1440.1140.1490.1610.1420.0050.0900.0290.0431.0001.000
TIPO_TRAT0.0920.1050.0751.0000.1270.1890.0550.0000.0840.0940.0241.0001.0000.1970.0930.0000.0690.0000.0230.0000.0790.0940.0000.0190.0870.0740.0000.1260.0180.0750.0940.0510.1440.0820.0000.0880.1550.1120.1000.0510.0000.4580.4150.0710.2250.0340.1860.0660.0890.1520.0800.0130.0980.0000.1170.000NaN0.0001.0000.0000.0000.0000.0001.0001.0001.0001.0001.0000.0680.0000.0951.0000.0001.0000.0470.0600.0510.0430.1360.0000.0930.0000.0001.0001.0000.0000.000NaN0.3280.4430.0000.3040.0000.0000.0280.0000.0801.0001.000

Missing values

2023-09-22T21:40:17.924173image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2023-09-22T21:40:23.244527image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-09-22T21:40:53.576279image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

DT_NOTIFICSEM_NOTDT_SIN_PRISEM_PRISG_UF_NOTID_REGIONACO_REGIONAID_MUNICIPCO_MUN_NOTID_UNIDADECO_UNI_NOTCS_SEXODT_NASCNU_IDADE_NTP_IDADECOD_IDADECS_GESTANTCS_RACACS_ESCOL_NID_PAISCO_PAISSG_UFID_RG_RESICO_RG_RESIID_MN_RESICO_MUN_RESCS_ZONASURTO_SGNOSOCOMIALAVE_SUINOFEBRETOSSEGARGANTADISPNEIADESC_RESPSATURACAODIARREIAVOMITOOUTRO_SINOUTRO_DESPUERPERAFATOR_RISCCARDIOPATIHEMATOLOGISIND_DOWNHEPATICAASMADIABETESNEUROLOGICPNEUMOPATIIMUNODEPRERENALOBESIDADEOBES_IMCOUT_MORBIMORB_DESCVACINADT_UT_DOSEMAE_VACDT_VAC_MAEM_AMAMENTADT_DOSEUNIDT_1_DOSEDT_2_DOSEANTIVIRALTP_ANTIVIROUT_ANTIVDT_ANTIVIRHOSPITALDT_INTERNASG_UF_INTEID_RG_INTECO_RG_INTEID_MN_INTECO_MU_INTEUTIDT_ENTUTIDT_SAIDUTISUPORT_VENRAIOX_RESRAIOX_OUTDT_RAIOXAMOSTRADT_COLETATP_AMOSTRAOUT_AMOSTPCR_RESULDT_PCRPOS_PCRFLUTP_FLU_PCRPCR_FLUASUFLUASU_OUTPCR_FLUBLIFLUBLI_OUTPOS_PCROUTPCR_VSRPCR_PARA1PCR_PARA2PCR_PARA3PCR_PARA4PCR_ADENOPCR_METAPPCR_BOCAPCR_RINOPCR_OUTRODS_PCR_OUTCLASSI_FINCLASSI_OUTCRITERIOEVOLUCAODT_EVOLUCADT_ENCERRADT_DIGITAHISTO_VGMPAIS_VGMCO_PS_VGMLO_PS_VGMDT_VGMDT_RT_VGMPCR_SARS2PAC_COCBOPAC_DSCBOOUT_ANIMDOR_ABDFADIGAPERD_OLFTPERD_PALATOMO_RESTOMO_OUTDT_TOMOTP_TES_ANDT_RES_ANRES_ANPOS_AN_FLUTP_FLU_ANPOS_AN_OUTAN_SARS2AN_VSRAN_PARA1AN_PARA2AN_PARA3AN_ADENOAN_OUTRODS_AN_OUTTP_AM_SORSOR_OUTDT_CO_SORTP_SOROUT_SORDT_RESRES_IGGRES_IGMRES_IGAESTRANGVACINA_COVDOSE_1_COVDOSE_2_COVDOSE_REFFAB_COV_1FAB_COV_2FAB_COVREFLAB_PR_COVLOTE_1_COVLOTE_2_COVLOTE_REFFNT_IN_COVDOSE_2REFFAB_COVRF2LOTE_REF2TRAT_COVTIPO_TRATOUT_TRATDT_TRT_COV
018/01/2023317/01/20233.0MGLEOPOLDINA1453ALEM PARAIBA310150HOSPITAL SAO SALVADOR2122677M19/06/19477533075699BRASIL1MGLEOPOLDINA1453ALEM PARAIBA310150.01NaN2.02.011.02.01.011.02.01.02NaN211222.02222.02.022NaNNaNNaN1NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN1NaNMGLEOPOLDINA1453ALEM PARAIBA3101502NaNNaN22NaN18/01/20232NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN4NaN2123/01/202331/01/202320/01/20230.0NaNNaNNaNNaNNaNNaNNaNNaNNaN212.02.06NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN2122/01/202110/02/202117/09/202186 - COVID-19 SINOVAC/BUTANTAN - CORONAVAC86 - COVID-19 SINOVAC/BUTANTAN - CORONAVAC87 - COVID-19 PFIZER - COMIRNATY86 - COVID-19 SINOVAC/BUTANTAN - CORONAVAC20201003120201003128235BD211/04/202287 - COVID-19 PFIZER - COMIRNATYFN9606NaNNaNNaNNaN
104/01/2023101/01/20231.0RJNaNNaNVOLTA REDONDA330630SECRETARIA MUNICIPAL DE SAUDE DE VOLTA REDONDA6086381M07/10/19556733067619BRASIL1RJNaNNaNVOLTA REDONDA330630.01NaN2.09.019.09.09.099.09.09.09NaN219999.09999.01.099NaN9NaN9NaNNaNNaNNaNNaNNaNNaN2NaNNaNNaN103/01/2023RJNaNNaNVOLTA REDONDA3306302NaNNaN95SEM LAUDO02/01/2023103/01/20234TR5NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN4NaN1118/01/202301/02/202323/01/20230.0NaNNaNNaNNaNNaNNaNNaNNaNNaN999.09.05SEM LAUDO04/01/2023203/01/20232.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN2120/04/2021NaNNaN85 - COVID-19 ASTRAZENECA/FIOCRUZ - COVISHIELDNaNNaN85 - COVID-19 ASTRAZENECA/FIOCRUZ - COVISHIELD213VCD025WNaNNaN210/05/202287 - COVID-19 PFIZER - COMIRNATYFP70822.0NaNNaNNaN
208/01/2023205/01/20231.0SPGVE XV BAURU1340JAU352530SANTA CASA DE JAU2791722F24/08/19507233072511BRASIL1SPGVE XV BAURU1340JAU352530.01NaN2.02.021.02.01.021.02.02.02NaN211222.02122.02.022NaN2NaNNaNNaNNaNNaNNaNNaNNaNNaN2NaNNaNNaN108/01/2023SPGVE XV BAURU1340JAU3525302NaNNaN2NaNNaNNaN107/01/20231NaN4NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN5NaN1112/01/202307/02/202325/01/20230.0NaNNaNNaNNaNNaNNaNNaNNaNNaN222.02.01NaN08/01/2023207/01/20231.02NaN1.01NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN126/03/202123/04/202106/11/202186 - COVID-19 SINOVAC/BUTANTAN - CORONAVAC86 - COVID-19 SINOVAC/BUTANTAN - CORONAVAC87 - COVID-19 PFIZER - COMIRNATY86 - COVID-19 SINOVAC/BUTANTAN - CORONAVAC210061210137FH8023219/04/202287 - COVID-19 PFIZER - COMIRNATYFN96062.0NaNNaNNaN
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23568031/08/20233526/08/202334.0SPGVE I CAPITAL1331SAO PAULO355030HOSPITAL INFANTIL SABARA6614426F24/05/202213300169NaNBRASIL1SPGVE I CAPITAL1331SAO PAULO355030.01NaN2.02.011.09.02.011.02.02.01CORIZANaN2NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN9NaNNaNNaNNaNNaNNaNNaN2NaNNaNNaN130/08/2023SPGVE I CAPITAL1331SAO PAULO355030130/08/202303/09/202321NaN30/08/2023130/08/20231NaN131/08/20232NaNNaNNaNNaNNaN11.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN2NaN1103/09/202308/09/202308/09/20230.0NaNNaNNaNNaNNaNNaNNaNNaNNaN929.09.06NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN2110/02/202310/03/2023NaN102 - COVID-19 PFIZER - COMIRNATY PEDIATRICA MENOR DE 5 ANOS102 - COVID-19 PFIZER - COMIRNATY PEDIATRICA MENOR DE 5 ANOSNaN102 - COVID-19 PFIZER - COMIRNATY PEDIATRICA MENOR DE 5 ANOSGC9016GC9016NaN2NaNNaNNaN2.0NaNNaNNaN
23568106/09/20233601/09/202335.0MGVARGINHA1466LAVRAS313820HOSPITAL VAZ MONTEIRO2112175M27/12/19329033090613BRASIL1MGVARGINHA1466LAVRAS313820.01NaN2.02.012.02.01.011.01.02.01PROSTRACAO. INAPETENCIA, DESIDNaN2NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN1NaNNaNNaNNaNNaNNaNNaN2NaNNaNNaN103/09/2023MGVARGINHA1466LAVRAS313820105/09/2023NaN19NaNNaN103/09/20231NaN4NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN5NaN1214/09/202315/09/202313/09/20230.0NaNNaNNaNNaNNaNNaNNaNNaNNaN222.02.06NaNNaN203/09/20231.02NaN1.01NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN2119/02/202109/03/202103/11/202186 - COVID-19 SINOVAC/BUTANTAN - CORONAVAC86 - COVID-19 SINOVAC/BUTANTAN - CORONAVAC87 - COVID-19 PFIZER - COMIRNATY86 - COVID-19 SINOVAC/BUTANTAN - CORONAVAC210017210017FG3535202/05/202288 - COVID-19 JANSSEN - AD26.COV2.S18757262.0NaNNaNNaN

Duplicate rows

Most frequently occurring

DT_NOTIFICSEM_NOTDT_SIN_PRISEM_PRISG_UF_NOTID_REGIONACO_REGIONAID_MUNICIPCO_MUN_NOTID_UNIDADECO_UNI_NOTCS_SEXODT_NASCNU_IDADE_NTP_IDADECOD_IDADECS_GESTANTCS_RACACS_ESCOL_NID_PAISCO_PAISSG_UFID_RG_RESICO_RG_RESIID_MN_RESICO_MUN_RESCS_ZONASURTO_SGNOSOCOMIALAVE_SUINOFEBRETOSSEGARGANTADISPNEIADESC_RESPSATURACAODIARREIAVOMITOOUTRO_SINOUTRO_DESPUERPERAFATOR_RISCCARDIOPATIHEMATOLOGISIND_DOWNHEPATICAASMADIABETESNEUROLOGICPNEUMOPATIIMUNODEPRERENALOBESIDADEOBES_IMCOUT_MORBIMORB_DESCVACINADT_UT_DOSEMAE_VACDT_VAC_MAEM_AMAMENTADT_DOSEUNIDT_1_DOSEDT_2_DOSEANTIVIRALTP_ANTIVIROUT_ANTIVDT_ANTIVIRHOSPITALDT_INTERNASG_UF_INTEID_RG_INTECO_RG_INTEID_MN_INTECO_MU_INTEUTIDT_ENTUTIDT_SAIDUTISUPORT_VENRAIOX_RESRAIOX_OUTDT_RAIOXAMOSTRADT_COLETATP_AMOSTRAOUT_AMOSTPCR_RESULDT_PCRPOS_PCRFLUTP_FLU_PCRPCR_FLUASUFLUASU_OUTPCR_FLUBLIFLUBLI_OUTPOS_PCROUTPCR_VSRPCR_PARA1PCR_PARA2PCR_PARA3PCR_PARA4PCR_ADENOPCR_METAPPCR_BOCAPCR_RINOPCR_OUTRODS_PCR_OUTCLASSI_FINCLASSI_OUTCRITERIOEVOLUCAODT_EVOLUCADT_ENCERRADT_DIGITAHISTO_VGMPAIS_VGMCO_PS_VGMLO_PS_VGMDT_VGMDT_RT_VGMPCR_SARS2PAC_COCBOPAC_DSCBOOUT_ANIMDOR_ABDFADIGAPERD_OLFTPERD_PALATOMO_RESTOMO_OUTDT_TOMOTP_TES_ANDT_RES_ANRES_ANPOS_AN_FLUTP_FLU_ANPOS_AN_OUTAN_SARS2AN_VSRAN_PARA1AN_PARA2AN_PARA3AN_ADENOAN_OUTRODS_AN_OUTTP_AM_SORSOR_OUTDT_CO_SORTP_SOROUT_SORDT_RESRES_IGGRES_IGMRES_IGAESTRANGVACINA_COVDOSE_1_COVDOSE_2_COVDOSE_REFFAB_COV_1FAB_COV_2FAB_COVREFLAB_PR_COVLOTE_1_COVLOTE_2_COVLOTE_REFFNT_IN_COVDOSE_2REFFAB_COVRF2LOTE_REF2TRAT_COVTIPO_TRATOUT_TRAT# duplicates
62501/08/20233131/07/202331.0SEREGIONAL ESTANCIA2057ESTANCIA280210HOSPITAL REGIONAL DE ESTANCIA JESSE FONTES6901743M09/05/201673300764NaNBRASIL1SEREGIONAL ESTANCIA2057ESTANCIA280210.01NaN2.02.011.02.01.012.02.02.0NaNNaNNaN2NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN2NaNNaNNaNNaNNaNNaNNaN2NaNNaNNaN101/08/2023SEREGIONAL ESTANCIA2057ESTANCIA2802102NaNNaN34NaN01/08/2023101/08/20231NaN203/08/2023NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN01/08/20230.0NaNNaNNaNNaNNaNNaNNaNNaNNaN222.02.06NaNNaNNaNNaN5.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN22NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN2NaNNaNNaN2.0NaNNaN4
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828010/07/20232809/07/202328.0MGBELO HORIZONTE1449BELO HORIZONTE310620HOSPITAL INFANTIL JOAO PAULO II26948M13/11/2022822008649BRASIL1MGBELO HORIZONTE1449BELO HORIZONTE310620.01NaN2.02.011.02.01.011.02.02.02NaNNaN2NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN109/07/2023MGBELO HORIZONTE1449BELO HORIZONTE3106202NaNNaNNaNNaNNaNNaN110/07/20231NaN4NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN4NaN1112/07/202323/08/202313/07/20230.0NaNNaNNaNNaNNaNNaNNaNNaNNaN222.02.0NaNNaNNaN2NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN22NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN2NaNNaNNaNNaNNaNNaN4
889011/05/20231909/05/202319.0SPGVE XVII CAMPINAS1342CAMPINAS350950UNIDADE DE PRONTO ATENDIMENTO SAO JOSE2023571F15/07/19645833058549BRASIL1SPGVE XVII CAMPINAS1342CAMPINAS350950.01NaN2.02.021.02.01.011.02.02.02NaN211222.02222.02.022NaN2NaN2NaNNaNNaNNaNNaNNaNNaN2NaNNaNNaN110/05/2023SPGVE XVII CAMPINAS1342CAMPINAS350950116/05/202322/07/202315DERRAME PELURAL10/05/20232NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN4NaN1322/07/202331/08/202311/05/20230.0NaNNaNNaNNaNNaNNaNNaNNaNNaN212.02.06NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN2122/05/202114/08/2021NaN85 - COVID-19 ASTRAZENECA/FIOCRUZ - COVISHIELD85 - COVID-19 ASTRAZENECA/FIOCRUZ - COVISHIELDNaN85 - COVID-19 ASTRAZENECA/FIOCRUZ - COVISHIELD214VCD047W216VCD198WNaN2NaNNaNNaN2.0NaNNaN4
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1172714/06/20232407/06/202323.0ACREGIONAL DO BAIXO ACRE1938RIO BRANCO120040FUNDHACRE2001586M10/10/19764633046641BRASIL1AMPURUS5585BOCA DO ACRE130070.01NaN2.02.012.02.01.011.02.02.02NaN212221.02122.02.022NaN1ENCEFALOPATIA HEPATICA2NaNNaNNaNNaNNaNNaNNaN2NaNNaNNaN109/06/2023ACREGIONAL DO BAIXO ACRE1938RIO BRANCO1200402NaNNaN26NaNNaN114/06/20231NaN114/06/2023NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN5NaN11NaN21/08/202314/08/20230.0NaNNaNNaNNaNNaNNaNNaNNaNNaN122.02.05AGUARDANDO RESULTADO13/06/2023NaN14/06/20235.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN2103/09/202117/11/2021NaN85 - COVID-19 ASTRAZENECA/FIOCRUZ - COVISHIELD85 - COVID-19 ASTRAZENECA/FIOCRUZ - COVISHIELDNaN85 - COVID-19 ASTRAZENECA/FIOCRUZ - COVISHIELD215VCD120W216VCD203ZNaN2NaNNaNNaN2.0NaNNaN4